library(MASS)
library(psy)
## Warning: package 'psy' was built under R version 3.3.2
library(lavaan)
## Warning: package 'lavaan' was built under R version 3.3.2
## This is lavaan 0.5-22
## lavaan is BETA software! Please report any bugs.
library(car)
## Warning: package 'car' was built under R version 3.3.2
library(semPlot)
## Warning: package 'semPlot' was built under R version 3.3.2
rm(list = ls()) ## clears global environment
cat("\014") ## clears screen
setwd("C:/users/evazquez/Downloads")
MainStudy<-read.csv("Main Study1.csv", skip=1, header=F) # reads pre-test 1 file and creates a data frame
NamesandHeaders<-read.csv("Main Study1.csv") # assigns headers and names to data frame
names(MainStudy)<-names(NamesandHeaders)
summary(MainStudy)
## X V6 X5 X6
## Min. : 1.0 162.233.200.114: 2 Min. :1.000 Min. :1.0
## 1st Qu.: 415.5 172.13.104.200 : 2 1st Qu.:5.000 1st Qu.:5.0
## Median : 936.0 174.57.22.159 : 2 Median :5.000 Median :6.0
## Mean :1121.0 192.133.84.5 : 2 Mean :5.755 Mean :5.9
## 3rd Qu.:1835.0 209.118.101.4 : 2 3rd Qu.:7.000 3rd Qu.:7.0
## Max. :2612.0 24.254.195.199 : 2 Max. :9.000 Max. :9.0
## (Other) :547
## X7 X8 X9 X10
## Min. :1.0 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:5.0 1st Qu.:5.000 1st Qu.:5.000 1st Qu.:1.000
## Median :5.0 Median :5.000 Median :5.000 Median :3.000
## Mean :5.2 Mean :5.717 Mean :5.705 Mean :3.157
## 3rd Qu.:6.0 3rd Qu.:7.000 3rd Qu.:7.000 3rd Qu.:5.000
## Max. :9.0 Max. :9.000 Max. :9.000 Max. :9.000
##
## X11 X12 X13 X14
## Min. :1.00 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:1.00 1st Qu.:1.000 1st Qu.:2.000 1st Qu.:2.000
## Median :2.00 Median :2.000 Median :5.000 Median :5.000
## Mean :3.05 Mean :2.964 Mean :4.048 Mean :4.349
## 3rd Qu.:5.00 3rd Qu.:5.000 3rd Qu.:6.000 3rd Qu.:6.000
## Max. :9.00 Max. :9.000 Max. :9.000 Max. :9.000
##
## X15 Group SEC SMP
## Min. :1.000 Min. :1.000 Credence :187 Facebook:189
## 1st Qu.:2.000 1st Qu.:3.000 Experience:159 Twitter :277
## Median :4.000 Median :6.000 Search :213 YouTube : 93
## Mean :4.039 Mean :5.156
## 3rd Qu.:6.000 3rd Qu.:7.000
## Max. :9.000 Max. :9.000
##
## FreqUseSMP Risk UsefulSMP BrandFam
## Min. :1.000 Min. :1.000 Min. :1.00 Min. :1.000
## 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:4.00 1st Qu.:1.000
## Median :5.000 Median :4.000 Median :6.00 Median :1.000
## Mean :4.349 Mean :4.055 Mean :5.39 Mean :1.429
## 3rd Qu.:6.000 3rd Qu.:6.000 3rd Qu.:7.00 3rd Qu.:2.000
## Max. :9.000 Max. :9.000 Max. :9.00 Max. :8.000
##
## PriceQuality TextVideo PeersExperts FreqPurchProduct
## Min. :1.0 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:5.0 1st Qu.:2.000 1st Qu.:3.000 1st Qu.:3.000
## Median :6.0 Median :5.000 Median :6.000 Median :5.000
## Mean :5.9 Mean :4.893 Mean :5.549 Mean :4.927
## 3rd Qu.:7.0 3rd Qu.:7.000 3rd Qu.:8.000 3rd Qu.:7.000
## Max. :9.0 Max. :9.000 Max. :9.000 Max. :9.000
##
## ProductImportance AnnualExpenses FreqPurchProductOnline
## Min. :1.000 Min. : 0.0000 Min. :1.000
## 1st Qu.:5.000 1st Qu.: 0.7738 1st Qu.:3.000
## Median :7.000 Median : 7.5000 Median :5.000
## Mean :6.095 Mean : 14.5872 Mean :4.671
## 3rd Qu.:8.000 3rd Qu.: 16.6667 3rd Qu.:7.000
## Max. :9.000 Max. :333.3333 Max. :9.000
##
## t1Stimuli t2Stimuli PageSubmitStimuli ClicksStimuli
## Min. : 0.963 Min. : 1.048 Min. :30.68 Min. : 1.000
## 1st Qu.: 5.863 1st Qu.: 6.556 1st Qu.:48.83 1st Qu.: 1.000
## Median : 9.530 Median : 10.947 Median :63.35 Median : 1.000
## Mean : 9.795 Mean : 18.958 Mean :62.31 Mean : 1.488
## 3rd Qu.:12.810 3rd Qu.: 17.017 3rd Qu.:73.10 3rd Qu.: 2.000
## Max. :24.193 Max. :244.500 Max. :98.63 Max. :24.000
##
## Age Gender Income Education
## Min. :18.00 Female:284 Min. :1.000 Min. : 5.00
## 1st Qu.:24.00 Male :275 1st Qu.:3.000 1st Qu.: 9.00
## Median :30.00 Median :4.000 Median :11.00
## Mean :31.82 Mean :4.326 Mean :10.57
## 3rd Qu.:37.00 3rd Qu.:6.000 3rd Qu.:12.00
## Max. :67.00 Max. :9.000 Max. :15.00
##
## RE WhyQ WhyP
## African American / Black: 64 Mode:logical Mode:logical
## Asian American : 39 NA's:559 NA's:559
## Caucasian / White :402
## Hispanic / Latino : 41
## Native American : 3
## Other : 10
##
## WhyW V6.1 t12_3 t7_2
## Mode:logical 162.233.200.114: 2 Min. : 5.357 Min. : 3.158
## NA's:559 172.13.104.200 : 2 1st Qu.: 8.659 1st Qu.: 14.074
## 174.57.22.159 : 2 Median : 10.681 Median : 19.103
## 192.133.84.5 : 2 Mean : 15.311 Mean : 20.927
## 209.118.101.4 : 2 3rd Qu.: 13.041 3rd Qu.: 25.304
## 24.254.195.199 : 2 Max. :1622.251 Max. :145.881
## (Other) :547
## copy5 copy6 copy7 copy8 copy9 copy10
## Min. :0 Min. :0 Min. :0 Min. :0 Min. :0 Min. :0
## 1st Qu.:0 1st Qu.:0 1st Qu.:0 1st Qu.:0 1st Qu.:0 1st Qu.:0
## Median :0 Median :0 Median :0 Median :0 Median :0 Median :0
## Mean :0 Mean :0 Mean :0 Mean :0 Mean :0 Mean :0
## 3rd Qu.:0 3rd Qu.:0 3rd Qu.:0 3rd Qu.:0 3rd Qu.:0 3rd Qu.:0
## Max. :0 Max. :0 Max. :0 Max. :0 Max. :0 Max. :0
##
## copy11 copy12 copy13 copy14 copy15 copyt8_3
## Min. :0 Min. :0 Min. :0 Min. :0 Min. :0 Min. :0
## 1st Qu.:0 1st Qu.:0 1st Qu.:0 1st Qu.:0 1st Qu.:0 1st Qu.:0
## Median :0 Median :0 Median :0 Median :0 Median :0 Median :0
## Mean :0 Mean :0 Mean :0 Mean :0 Mean :0 Mean :0
## 3rd Qu.:0 3rd Qu.:0 3rd Qu.:0 3rd Qu.:0 3rd Qu.:0 3rd Qu.:0
## Max. :0 Max. :0 Max. :0 Max. :0 Max. :0 Max. :0
##
## Threshold X...V1 LocationLatitude
## Min. : 94.42 R_007qxXfK2MGkAOp: 1 Min. :14.55
## 1st Qu.:151.46 R_00wCAplOFL5UsN7: 1 1st Qu.:33.75
## Median :186.27 R_01AbyHf6nvFjGIt: 1 Median :38.40
## Mean :196.52 R_02FG1WiUYaRg9Dv: 1 Mean :37.52
## 3rd Qu.:231.71 R_02LiubfeJYfWugd: 1 3rd Qu.:41.49
## Max. :561.13 R_03AwpbV0Mh4RDBX: 1 Max. :61.32
## (Other) :553
## LocationLongitude Quality PurchInt WOM
## Min. :-157.82 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.: -96.99 1st Qu.:5.000 1st Qu.:1.333 1st Qu.:2.000
## Median : -86.46 Median :5.600 Median :2.333 Median :4.333
## Mean : -89.00 Mean :5.655 Mean :3.057 Mean :4.145
## 3rd Qu.: -79.72 3rd Qu.:6.600 3rd Qu.:4.500 3rd Qu.:5.833
## Max. : 121.04 Max. :9.000 Max. :9.000 Max. :9.000
##
## Alignment GenderVal PrevExpwithSMP State
## Min. :0.0000 Min. :0.0000 Min. :1.000 California: 58
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:3.500 Texas : 44
## Median :0.0000 Median :0.0000 Median :5.000 New York : 33
## Mean :0.4919 Mean :0.4919 Mean :4.869 Illinois : 32
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:6.500 Florida : 30
## Max. :1.0000 Max. :1.0000 Max. :9.000 Ohio : 24
## (Other) :338
## City StateID CityID Frmwrk1
## Glendale : 7 5 : 58 Min. : 1.0 Min. :1.000
## New York : 7 44 : 44 1st Qu.: 77.0 1st Qu.:4.000
## Unspecified : 7 33 : 33 Median :152.0 Median :6.000
## Englewood : 6 14 : 32 Mean :165.3 Mean :5.728
## Fort Worth : 6 10 : 30 3rd Qu.:252.0 3rd Qu.:8.000
## Jacksonville: 6 36 : 24 Max. :378.0 Max. :9.000
## (Other) :520 (Other):338
## Frmwrk2 Frmwrk3 IR1 IR2
## Min. :1.000 Min. :1.000 Min. :0.000 Min. :0.00
## 1st Qu.:3.000 1st Qu.:3.000 1st Qu.:0.000 1st Qu.:0.00
## Median :4.000 Median :4.000 Median :0.000 Median :0.00
## Mean :4.494 Mean :4.249 Mean :2.517 Mean :1.47
## 3rd Qu.:7.000 3rd Qu.:6.000 3rd Qu.:7.000 3rd Qu.:3.00
## Max. :9.000 Max. :9.000 Max. :9.000 Max. :9.00
##
## IR3 IR4 IR5 IR6
## Min. :0.000 Min. :0.000 Min. :0.000 Min. :0.000
## 1st Qu.:0.000 1st Qu.:0.000 1st Qu.:0.000 1st Qu.:0.000
## Median :0.000 Median :0.000 Median :0.000 Median :0.000
## Mean :1.814 Mean :1.943 Mean :1.066 Mean :1.494
## 3rd Qu.:4.000 3rd Qu.:5.000 3rd Qu.:2.000 3rd Qu.:3.000
## Max. :9.000 Max. :9.000 Max. :9.000 Max. :9.000
##
## SP1 SP2 SP3 SP4
## Min. :0.000 Min. :0.000 Min. :0.0 Min. :0.000
## 1st Qu.:0.000 1st Qu.:0.000 1st Qu.:0.0 1st Qu.:0.000
## Median :0.000 Median :0.000 Median :0.0 Median :0.000
## Mean :1.989 Mean :1.701 Mean :1.8 Mean :1.682
## 3rd Qu.:4.000 3rd Qu.:3.000 3rd Qu.:3.0 3rd Qu.:3.000
## Max. :9.000 Max. :9.000 Max. :9.0 Max. :9.000
##
## SP5 SP6 SP7 SP8
## Min. :0.000 Min. :0.000 Min. :0.000 Min. :0.000
## 1st Qu.:0.000 1st Qu.:0.000 1st Qu.:0.000 1st Qu.:0.000
## Median :0.000 Median :0.000 Median :0.000 Median :0.000
## Mean :1.415 Mean :1.476 Mean :1.791 Mean :1.465
## 3rd Qu.:2.000 3rd Qu.:2.000 3rd Qu.:3.000 3rd Qu.:2.000
## Max. :9.000 Max. :9.000 Max. :9.000 Max. :9.000
##
## SP9 SP10 SP11 SP12
## Min. :0.000 Min. :0.000 Min. :0.000 Min. :0.0000
## 1st Qu.:0.000 1st Qu.:0.000 1st Qu.:0.000 1st Qu.:0.0000
## Median :0.000 Median :0.000 Median :0.000 Median :0.0000
## Mean :1.556 Mean :1.413 Mean :0.907 Mean :0.9732
## 3rd Qu.:2.000 3rd Qu.:1.500 3rd Qu.:1.000 3rd Qu.:1.0000
## Max. :9.000 Max. :9.000 Max. :9.000 Max. :9.0000
##
## TS1 TS2 TS3 TS4
## Min. :0.000 Min. :0.00 Min. :0.00 Min. :0.000
## 1st Qu.:0.000 1st Qu.:0.00 1st Qu.:0.00 1st Qu.:0.000
## Median :0.000 Median :0.00 Median :0.00 Median :0.000
## Mean :2.671 Mean :1.64 Mean :1.64 Mean :2.667
## 3rd Qu.:7.000 3rd Qu.:3.00 3rd Qu.:3.00 3rd Qu.:7.000
## Max. :9.000 Max. :9.00 Max. :9.00 Max. :9.000
##
## TS5 TS6 TS7 TS8
## Min. :0.000 Min. :0.0000 Min. :0.000 Min. :0.000
## 1st Qu.:0.000 1st Qu.:0.0000 1st Qu.:0.000 1st Qu.:0.000
## Median :0.000 Median :0.0000 Median :0.000 Median :0.000
## Mean :1.349 Mean :0.9803 Mean :2.705 Mean :1.336
## 3rd Qu.:2.000 3rd Qu.:1.0000 3rd Qu.:7.000 3rd Qu.:2.000
## Max. :9.000 Max. :9.0000 Max. :9.000 Max. :9.000
##
## TS9
## Min. :0.0000
## 1st Qu.:0.0000
## Median :0.0000
## Mean :0.8819
## 3rd Qu.:1.0000
## Max. :9.0000
##
MainStudySearch<-subset(MainStudy,MainStudy$Group==7|MainStudy$Group==9)
MainStudyExperience<-subset(MainStudy,MainStudy$Group==4|MainStudy$Group==6)
## MainStudyExperience$Quality<-ifelse(MainStudyExperience$SMP=="Facebook",MainStudyExperience$Quality*1.12,MainStudyExperience$Quality) ## Adjustment due to foreign language exposure
MainStudyCredence<-subset(MainStudy,MainStudy$Group==1|MainStudy$Group==3)
Age<-t.test(Age~SMP,data=MainStudySearch)
Gender<-chisq.test(MainStudySearch$SMP,MainStudySearch$Gender)
Income<-t.test(Income~SMP,data=MainStudySearch)
Education<-t.test(Education~SMP,data=MainStudySearch)
RE<-chisq.test(MainStudySearch$SMP,MainStudySearch$RE,simulate.p.value=T)
StimuliTime<-t.test(PageSubmitStimuli~SMP,data=MainStudySearch,mu=1)
FreqUseSMP<-t.test(FreqUseSMP~SMP,data=MainStudySearch)
Risk<-t.test(Risk~SMP,data=MainStudySearch)
UsefulSMP<-t.test(UsefulSMP~SMP,data=MainStudySearch)
BrandFam<-t.test(BrandFam~SMP,data=MainStudySearch)
PriceQuality<-t.test(PriceQuality~SMP,data=MainStudySearch)
TextVideo<-t.test(TextVideo~SMP,data=MainStudySearch)
PeersExperts<-t.test(PeersExperts~SMP,data=MainStudySearch)
FreqPurchProduct<-t.test(FreqPurchProduct~SMP,data=MainStudySearch)
ProductImportance<-t.test(ProductImportance~SMP,data=MainStudySearch)
AnnualExpenses<-t.test(AnnualExpenses~SMP,data=MainStudySearch)
FreqPurchProductOnline<-t.test(FreqPurchProductOnline~SMP,data=MainStudySearch)
t1Stimuli<-t.test(t1Stimuli~SMP,data=MainStudySearch)
t2Stimuli<-t.test(t2Stimuli~SMP,data=MainStudySearch)
PageSubmitStimuli<-t.test(PageSubmitStimuli~SMP,data=MainStudySearch)
ClicksStimuli<-t.test(ClicksStimuli~SMP,data=MainStudySearch)
Threshold<-t.test(Threshold~SMP,data=MainStudySearch)
Longitude<-t.test(LocationLongitude~SMP,data=MainStudySearch)
Latitude<-t.test(LocationLatitude~SMP,data=MainStudySearch)
PrevExpwithSMP<-t.test(PrevExpwithSMP~SMP,data=MainStudySearch)
TS1<-t.test(TS1~SMP,data=MainStudySearch)
TS2<-t.test(TS2~SMP,data=MainStudySearch)
TS3<-t.test(TS3~SMP,data=MainStudySearch)
TS4<-t.test(TS4~SMP,data=MainStudySearch)
TS5<-t.test(TS5~SMP,data=MainStudySearch)
TS6<-t.test(TS6~SMP,data=MainStudySearch)
TS7<-t.test(TS7~SMP,data=MainStudySearch)
TS8<-t.test(TS8~SMP,data=MainStudySearch)
TS9<-t.test(TS9~SMP,data=MainStudySearch)
Frmwrk1<-t.test(Frmwrk1~SMP,data=MainStudySearch)
Frmwrk2<-t.test(Frmwrk2~SMP,data=MainStudySearch)
Frmwrk3<-t.test(Frmwrk3~SMP,data=MainStudySearch)
controls<-t(data.frame(Age$p.value,Gender$p.value,Income$p.value,Education$p.value,RE$p.value,StimuliTime$p.value,FreqUseSMP$p.value,Risk$p.value,UsefulSMP$p.value,BrandFam$p.value,PriceQuality$p.value,TextVideo$p.value,PeersExperts$p.value,FreqPurchProduct$p.value,ProductImportance$p.value,AnnualExpenses$p.value,FreqPurchProductOnline$p.value,t1Stimuli$p.value,t2Stimuli$p.value,PageSubmitStimuli$p.value,ClicksStimuli$p.value,Threshold$p.value,Longitude$p.value,Latitude$p.value,PrevExpwithSMP$p.value,
TS1$p.value,TS2$p.value,TS3$p.value,TS4$p.value,TS5$p.value,TS6$p.value,
TS7$p.value,TS8$p.value,TS9$p.value,
Frmwrk1$p.value,Frmwrk2$p.value,Frmwrk3$p.value))
subset(controls,controls<0.1)
## [,1]
## FreqUseSMP.p.value 9.422638e-05
## UsefulSMP.p.value 4.821876e-02
## FreqPurchProductOnline.p.value 8.654736e-02
## ClicksStimuli.p.value 5.339581e-02
## PrevExpwithSMP.p.value 8.860254e-04
## TS1.p.value 2.690715e-02
## TS4.p.value 6.606772e-02
leveneTest(Quality~SMP,data=MainStudySearch,center=mean)
## Levene's Test for Homogeneity of Variance (center = mean)
## Df F value Pr(>F)
## group 1 1.1447 0.2859
## 211
t.test(Quality~SMP,data=MainStudySearch,var.equal=T) ## Hypothesis 1
##
## Two Sample t-test
##
## data: Quality by SMP
## t = -3.631, df = 211, p-value = 0.0003544
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -1.089402 -0.322743
## sample estimates:
## mean in group Facebook mean in group Twitter
## 5.503636 6.209709
wilcox.test(Quality~SMP,data=MainStudySearch)
##
## Wilcoxon rank sum test with continuity correction
##
## data: Quality by SMP
## W = 4321.5, p-value = 0.002749
## alternative hypothesis: true location shift is not equal to 0
Model<-'FreqUseSMP ~ Alignment
TS1 ~ Alignment
Quality ~ FreqUseSMP + Alignment + FreqPurchProductOnline+ClicksStimuli+TS1+Frmwrk3*Frmwrk1
PurchInt ~ Quality+Alignment+FreqUseSMP + FreqPurchProductOnline+ClicksStimuli+TS1+Frmwrk3*Frmwrk1
WOM ~ Quality+Alignment+FreqUseSMP+FreqPurchProductOnline+ClicksStimuli+TS1+Frmwrk3*Frmwrk1'
fit<-sem(Model,data=MainStudySearch)
## Found more than one class "Model" in cache; using the first, from namespace 'lavaan'
fitMeasures(fit)
## npar fmin chisq
## 26.000 0.052 22.034
## df pvalue baseline.chisq
## 9.000 0.009 353.851
## baseline.df baseline.pvalue cfi
## 30.000 0.000 0.960
## tli nnfi rfi
## 0.866 0.866 0.792
## nfi pnfi ifi
## 0.938 0.281 0.962
## rni logl unrestricted.logl
## 0.960 -3405.421 -3394.404
## aic bic ntotal
## 6862.842 6950.236 213.000
## bic2 rmsea rmsea.ci.lower
## 6867.850 0.082 0.039
## rmsea.ci.upper rmsea.pvalue rmr
## 0.127 0.099 0.158
## rmr_nomean srmr srmr_bentler
## 0.158 0.046 0.046
## srmr_bentler_nomean srmr_bollen srmr_bollen_nomean
## 0.046 0.046 0.046
## srmr_mplus srmr_mplus_nomean cn_05
## 0.046 0.046 164.554
## cn_01 gfi agfi
## 210.443 0.960 0.798
## pgfi mfi ecvi
## 0.192 0.970 0.348
summary(fit,standardized=T,fit.measures=T,rsq=T)
## lavaan (0.5-22) converged normally after 43 iterations
##
## Number of observations 213
##
## Estimator ML
## Minimum Function Test Statistic 22.034
## Degrees of freedom 9
## P-value (Chi-square) 0.009
##
## Model test baseline model:
##
## Minimum Function Test Statistic 353.851
## Degrees of freedom 30
## P-value 0.000
##
## User model versus baseline model:
##
## Comparative Fit Index (CFI) 0.960
## Tucker-Lewis Index (TLI) 0.866
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -3405.421
## Loglikelihood unrestricted model (H1) -3394.404
##
## Number of free parameters 26
## Akaike (AIC) 6862.842
## Bayesian (BIC) 6950.236
## Sample-size adjusted Bayesian (BIC) 6867.850
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.082
## 90 Percent Confidence Interval 0.039 0.127
## P-value RMSEA <= 0.05 0.099
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.046
##
## Parameter Estimates:
##
## Information Expected
## Standard Errors Standard
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## FreqUseSMP ~
## Algnmnt -1.193 0.297 -4.019 0.000 -1.193 -0.265
## TS1 ~
## Algnmnt 0.471 0.211 2.226 0.026 0.471 0.151
## Quality ~
## FrqUSMP 0.089 0.044 2.027 0.043 0.089 0.135
## Algnmnt 0.741 0.202 3.667 0.000 0.741 0.251
## FrqPrPO -0.008 0.049 -0.163 0.870 -0.008 -0.011
## ClcksSt 0.026 0.086 0.298 0.766 0.026 0.020
## TS1 0.133 0.062 2.151 0.031 0.133 0.140
## Frmwrk1 (Frm3) -0.092 0.030 -3.056 0.002 -0.092 -0.145
## PurchInt ~
## Quality 0.610 0.081 7.493 0.000 0.610 0.454
## Algnmnt 0.229 0.249 0.920 0.358 0.229 0.058
## FrqUSMP 0.172 0.053 3.244 0.001 0.172 0.195
## FrqPrPO 0.118 0.059 2.006 0.045 0.118 0.117
## ClcksSt -0.024 0.103 -0.228 0.819 -0.024 -0.013
## TS1 -0.124 0.075 -1.667 0.096 -0.124 -0.098
## Frmwrk1 (Frm3) -0.092 0.030 -3.056 0.002 -0.092 -0.107
## WOM ~
## Quality 0.817 0.081 10.151 0.000 0.817 0.551
## Algnmnt 0.709 0.247 2.878 0.004 0.709 0.162
## FrqUSMP 0.190 0.052 3.614 0.000 0.190 0.195
## FrqPrPO -0.071 0.058 -1.220 0.222 -0.071 -0.064
## ClcksSt 0.029 0.102 0.287 0.774 0.029 0.015
## TS1 -0.004 0.074 -0.051 0.960 -0.004 -0.003
## Frmwrk1 (Frm3) -0.092 0.030 -3.056 0.002 -0.092 -0.098
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .PurchInt ~~
## .WOM 1.626 0.217 7.478 0.000 1.626 0.597
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .FreqUseSMP 4.688 0.454 10.320 0.000 4.688 0.930
## .TS1 2.377 0.230 10.320 0.000 2.377 0.977
## .Quality 1.924 0.186 10.320 0.000 1.924 0.885
## .PurchInt 2.757 0.267 10.320 0.000 2.757 0.701
## .WOM 2.695 0.261 10.320 0.000 2.695 0.564
##
## R-Square:
## Estimate
## FreqUseSMP 0.070
## TS1 0.023
## Quality 0.115
## PurchInt 0.299
## WOM 0.436
coef(fit)
## FreqUseSMP~Alignment TS1~Alignment
## -1.193 0.471
## Quality~FreqUseSMP Quality~Alignment
## 0.089 0.741
## Quality~FreqPurchProductOnline Quality~ClicksStimuli
## -0.008 0.026
## Quality~TS1 Frmwrk3
## 0.133 -0.092
## PurchInt~Quality PurchInt~Alignment
## 0.610 0.229
## PurchInt~FreqUseSMP PurchInt~FreqPurchProductOnline
## 0.172 0.118
## PurchInt~ClicksStimuli PurchInt~TS1
## -0.024 -0.124
## Frmwrk3 WOM~Quality
## -0.092 0.817
## WOM~Alignment WOM~FreqUseSMP
## 0.709 0.190
## WOM~FreqPurchProductOnline WOM~ClicksStimuli
## -0.071 0.029
## WOM~TS1 Frmwrk3
## -0.004 -0.092
## FreqUseSMP~~FreqUseSMP TS1~~TS1
## 4.688 2.377
## Quality~~Quality PurchInt~~PurchInt
## 1.924 2.757
## WOM~~WOM PurchInt~~WOM
## 2.695 1.626
standardizedSolution(fit)
## lhs op rhs est.std se z
## 1 FreqUseSMP ~ Alignment -0.265 0.063 -4.244
## 2 TS1 ~ Alignment 0.151 0.067 2.265
## 3 Quality ~ FreqUseSMP 0.135 0.066 2.042
## 4 Quality ~ Alignment 0.251 0.066 3.825
## 5 Quality ~ FreqPurchProductOnline -0.011 0.065 -0.163
## 6 Quality ~ ClicksStimuli 0.020 0.065 0.298
## 7 Quality ~ TS1 0.140 0.065 2.170
## 8 Quality ~ Frmwrk1 -0.145 0.047 -3.087
## 9 PurchInt ~ Quality 0.454 0.055 8.295
## 10 PurchInt ~ Alignment 0.058 0.063 0.922
## 11 PurchInt ~ FreqUseSMP 0.195 0.059 3.281
## 12 PurchInt ~ FreqPurchProductOnline 0.117 0.058 2.024
## 13 PurchInt ~ ClicksStimuli -0.013 0.058 -0.228
## 14 PurchInt ~ TS1 -0.098 0.058 -1.671
## 15 PurchInt ~ Frmwrk1 -0.107 0.035 -3.092
## 16 WOM ~ Quality 0.551 0.047 11.831
## 17 WOM ~ Alignment 0.162 0.056 2.914
## 18 WOM ~ FreqUseSMP 0.195 0.054 3.633
## 19 WOM ~ FreqPurchProductOnline -0.064 0.052 -1.223
## 20 WOM ~ ClicksStimuli 0.015 0.052 0.287
## 21 WOM ~ TS1 -0.003 0.053 -0.051
## 22 WOM ~ Frmwrk1 -0.098 0.032 -3.095
## 23 FreqUseSMP ~~ FreqUseSMP 0.930 0.033 27.985
## 24 TS1 ~~ TS1 0.977 0.020 48.664
## 25 Quality ~~ Quality 0.885 0.039 22.800
## 26 PurchInt ~~ PurchInt 0.701 0.052 13.480
## 27 WOM ~~ WOM 0.564 0.051 11.168
## 28 PurchInt ~~ WOM 0.597 0.044 13.521
## 29 Alignment ~~ Alignment 1.000 0.000 NA
## 30 Alignment ~~ FreqPurchProductOnline 0.118 0.000 NA
## 31 Alignment ~~ ClicksStimuli 0.136 0.000 NA
## 32 Alignment ~~ Frmwrk1 -0.011 0.000 NA
## 33 FreqPurchProductOnline ~~ FreqPurchProductOnline 1.000 0.000 NA
## 34 FreqPurchProductOnline ~~ ClicksStimuli 0.117 0.000 NA
## 35 FreqPurchProductOnline ~~ Frmwrk1 0.004 0.000 NA
## 36 ClicksStimuli ~~ ClicksStimuli 1.000 0.000 NA
## 37 ClicksStimuli ~~ Frmwrk1 -0.059 0.000 NA
## 38 Frmwrk1 ~~ Frmwrk1 1.000 0.000 NA
## pvalue
## 1 0.000
## 2 0.024
## 3 0.041
## 4 0.000
## 5 0.870
## 6 0.766
## 7 0.030
## 8 0.002
## 9 0.000
## 10 0.357
## 11 0.001
## 12 0.043
## 13 0.819
## 14 0.095
## 15 0.002
## 16 0.000
## 17 0.004
## 18 0.000
## 19 0.221
## 20 0.774
## 21 0.960
## 22 0.002
## 23 0.000
## 24 0.000
## 25 0.000
## 26 0.000
## 27 0.000
## 28 0.000
## 29 NA
## 30 NA
## 31 NA
## 32 NA
## 33 NA
## 34 NA
## 35 NA
## 36 NA
## 37 NA
## 38 NA
# semPaths(fit,"std",edge.label.cex=1,curvePivot=T,covAtResiduals=F,residuals=F,fade=F)
inspect(fit,"theta")
## FrUSMP TS1 Qualty PrchIn WOM Algnmn FrqPPO
## FreqUseSMP 4.688
## TS1 0.000 2.377
## Quality 0.000 0.000 1.924
## PurchInt 0.000 0.000 0.000 2.757
## WOM 0.000 0.000 0.000 1.626 2.695
## Alignment 0.000 0.000 0.000 0.000 0.000 0.250
## FreqPurchProductOnline 0.000 0.000 0.000 0.000 0.000 0.115 3.824
## ClicksStimuli 0.000 0.000 0.000 0.000 0.000 0.076 0.256
## Frmwrk1 0.000 0.000 0.000 0.000 0.000 -0.013 0.020
## ClcksS Frmwr1
## FreqUseSMP
## TS1
## Quality
## PurchInt
## WOM
## Alignment
## FreqPurchProductOnline
## ClicksStimuli 1.254
## Frmwrk1 -0.154 5.314
Age<-t.test(Age~SMP,data=MainStudyExperience)
Gender<-chisq.test(MainStudyExperience$SMP,MainStudyExperience$Gender)
Income<-t.test(Income~SMP,data=MainStudyExperience)
Education<-t.test(Education~SMP,data=MainStudyExperience)
RE<-chisq.test(MainStudyExperience$SMP,MainStudyExperience$RE,simulate.p.value=T)
StimuliTime<-t.test(PageSubmitStimuli~SMP,data=MainStudyExperience,mu=1)
FreqUseSMP<-t.test(FreqUseSMP~SMP,data=MainStudyExperience)
Risk<-t.test(Risk~SMP,data=MainStudyExperience)
UsefulSMP<-t.test(UsefulSMP~SMP,data=MainStudyExperience)
BrandFam<-t.test(BrandFam~SMP,data=MainStudyExperience)
PriceQuality<-t.test(PriceQuality~SMP,data=MainStudyExperience)
TextVideo<-t.test(TextVideo~SMP,data=MainStudyExperience)
PeersExperts<-t.test(PeersExperts~SMP,data=MainStudyExperience)
FreqPurchProduct<-t.test(FreqPurchProduct~SMP,data=MainStudyExperience)
ProductImportance<-t.test(ProductImportance~SMP,data=MainStudyExperience)
AnnualExpenses<-t.test(AnnualExpenses~SMP,data=MainStudyExperience)
FreqPurchProductOnline<-t.test(FreqPurchProductOnline~SMP,data=MainStudyExperience)
t1Stimuli<-t.test(t1Stimuli~SMP,data=MainStudyExperience)
t2Stimuli<-t.test(t2Stimuli~SMP,data=MainStudyExperience)
PageSubmitStimuli<-t.test(PageSubmitStimuli~SMP,data=MainStudyExperience)
ClicksStimuli<-t.test(ClicksStimuli~SMP,data=MainStudyExperience)
Threshold<-t.test(Threshold~SMP,data=MainStudyExperience)
Longitude<-t.test(LocationLongitude~SMP,data=MainStudyExperience)
Latitude<-t.test(LocationLatitude~SMP,data=MainStudyExperience)
controls<-t(data.frame(Age$p.value,Gender$p.value,Income$p.value,Education$p.value,RE$p.value,StimuliTime$p.value,FreqUseSMP$p.value,Risk$p.value,UsefulSMP$p.value,BrandFam$p.value,PriceQuality$p.value,TextVideo$p.value,PeersExperts$p.value,FreqPurchProduct$p.value,ProductImportance$p.value,AnnualExpenses$p.value,FreqPurchProductOnline$p.value,t1Stimuli$p.value,t2Stimuli$p.value,PageSubmitStimuli$p.value,ClicksStimuli$p.value,Threshold$p.value,Longitude$p.value,Latitude$p.value))
subset(controls,controls<0.1)
## [,1]
## FreqUseSMP.p.value 0.002562305
## PriceQuality.p.value 0.059148340
leveneTest(Quality~SMP,data=MainStudyExperience,center=mean)
## Levene's Test for Homogeneity of Variance (center = mean)
## Df F value Pr(>F)
## group 1 0.0924 0.7616
## 157
t.test(Quality~SMP,data=MainStudyExperience,var.equal=T) ## Hypothesis 2
##
## Two Sample t-test
##
## data: Quality by SMP
## t = 0.26824, df = 157, p-value = 0.7889
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.3209922 0.4218783
## sample estimates:
## mean in group Facebook mean in group Twitter
## 5.835443 5.785000
wilcox.test(Quality~SMP,data=MainStudyExperience)
##
## Wilcoxon rank sum test with continuity correction
##
## data: Quality by SMP
## W = 3228.5, p-value = 0.8141
## alternative hypothesis: true location shift is not equal to 0
Model<-'FreqUseSMP ~ Alignment
Quality ~ FreqUseSMP + Alignment + PriceQuality
PurchInt ~ Quality+Alignment+FreqUseSMP + PriceQuality
WOM ~ Quality+Alignment+FreqUseSMP+PriceQuality'
fit<-sem(Model,data=MainStudyExperience)
fitMeasures(fit)
## npar fmin chisq
## 17.000 0.014 4.587
## df pvalue baseline.chisq
## 1.000 0.032 186.823
## baseline.df baseline.pvalue cfi
## 14.000 0.000 0.979
## tli nnfi rfi
## 0.709 0.709 0.656
## nfi pnfi ifi
## 0.975 0.070 0.981
## rni logl unrestricted.logl
## 0.979 -1623.794 -1621.501
## aic bic ntotal
## 3281.588 3333.760 159.000
## bic2 rmsea rmsea.ci.lower
## 3279.945 0.150 0.036
## rmsea.ci.upper rmsea.pvalue rmr
## 0.300 0.068 0.157
## rmr_nomean srmr srmr_bentler
## 0.157 0.037 0.037
## srmr_bentler_nomean srmr_bollen srmr_bollen_nomean
## 0.037 0.037 0.037
## srmr_mplus srmr_mplus_nomean cn_05
## 0.037 0.037 134.165
## cn_01 gfi agfi
## 231.000 0.986 0.706
## pgfi mfi ecvi
## 0.047 0.989 0.243
summary(fit,standardized=T,fit.measures=T,rsq=T)
## lavaan (0.5-22) converged normally after 39 iterations
##
## Number of observations 159
##
## Estimator ML
## Minimum Function Test Statistic 4.587
## Degrees of freedom 1
## P-value (Chi-square) 0.032
##
## Model test baseline model:
##
## Minimum Function Test Statistic 186.823
## Degrees of freedom 14
## P-value 0.000
##
## User model versus baseline model:
##
## Comparative Fit Index (CFI) 0.979
## Tucker-Lewis Index (TLI) 0.709
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -1623.794
## Loglikelihood unrestricted model (H1) -1621.501
##
## Number of free parameters 17
## Akaike (AIC) 3281.588
## Bayesian (BIC) 3333.760
## Sample-size adjusted Bayesian (BIC) 3279.945
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.150
## 90 Percent Confidence Interval 0.036 0.300
## P-value RMSEA <= 0.05 0.068
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.037
##
## Parameter Estimates:
##
## Information Expected
## Standard Errors Standard
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## FreqUseSMP ~
## Alignment 0.997 0.323 3.086 0.002 0.997 0.238
## Quality ~
## FreqUseSMP 0.106 0.045 2.351 0.019 0.106 0.189
## Alignment -0.048 0.191 -0.251 0.802 -0.048 -0.020
## PriceQuality 0.012 0.045 0.259 0.796 0.012 0.020
## PurchInt ~
## Quality 0.602 0.119 5.076 0.000 0.602 0.369
## Alignment -0.071 0.286 -0.249 0.803 -0.071 -0.019
## FreqUseSMP 0.107 0.069 1.566 0.117 0.107 0.117
## PriceQuality 0.142 0.068 2.085 0.037 0.142 0.151
## WOM ~
## Quality 0.924 0.115 8.007 0.000 0.924 0.542
## Alignment 0.198 0.278 0.713 0.476 0.198 0.049
## FreqUseSMP -0.029 0.067 -0.436 0.663 -0.029 -0.030
## PriceQuality 0.065 0.066 0.977 0.328 0.065 0.066
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .PurchInt ~~
## .WOM 1.799 0.272 6.623 0.000 1.799 0.617
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .FreqUseSMP 4.150 0.465 8.916 0.000 4.150 0.943
## .Quality 1.339 0.150 8.916 0.000 1.339 0.966
## .PurchInt 2.998 0.336 8.916 0.000 2.998 0.811
## .WOM 2.834 0.318 8.916 0.000 2.834 0.704
##
## R-Square:
## Estimate
## FreqUseSMP 0.057
## Quality 0.034
## PurchInt 0.189
## WOM 0.296
coef(fit)
## FreqUseSMP~Alignment Quality~FreqUseSMP Quality~Alignment
## 0.997 0.106 -0.048
## Quality~PriceQuality PurchInt~Quality PurchInt~Alignment
## 0.012 0.602 -0.071
## PurchInt~FreqUseSMP PurchInt~PriceQuality WOM~Quality
## 0.107 0.142 0.924
## WOM~Alignment WOM~FreqUseSMP WOM~PriceQuality
## 0.198 -0.029 0.065
## FreqUseSMP~~FreqUseSMP Quality~~Quality PurchInt~~PurchInt
## 4.150 1.339 2.998
## WOM~~WOM PurchInt~~WOM
## 2.834 1.799
standardizedSolution(fit)
## lhs op rhs est.std se z pvalue
## 1 FreqUseSMP ~ Alignment 0.238 0.074 3.223 0.001
## 2 Quality ~ FreqUseSMP 0.189 0.079 2.391 0.017
## 3 Quality ~ Alignment -0.020 0.081 -0.251 0.802
## 4 Quality ~ PriceQuality 0.020 0.079 0.259 0.796
## 5 PurchInt ~ Quality 0.369 0.068 5.429 0.000
## 6 PurchInt ~ Alignment -0.019 0.074 -0.249 0.803
## 7 PurchInt ~ FreqUseSMP 0.117 0.074 1.574 0.115
## 8 PurchInt ~ PriceQuality 0.151 0.071 2.118 0.034
## 9 WOM ~ Quality 0.542 0.057 9.445 0.000
## 10 WOM ~ Alignment 0.049 0.069 0.714 0.475
## 11 WOM ~ FreqUseSMP -0.030 0.070 -0.436 0.663
## 12 WOM ~ PriceQuality 0.066 0.067 0.980 0.327
## 13 FreqUseSMP ~~ FreqUseSMP 0.943 0.035 26.905 0.000
## 14 Quality ~~ Quality 0.966 0.028 33.991 0.000
## 15 PurchInt ~~ PurchInt 0.811 0.056 14.552 0.000
## 16 WOM ~~ WOM 0.704 0.061 11.584 0.000
## 17 PurchInt ~~ WOM 0.617 0.049 12.576 0.000
## 18 Alignment ~~ Alignment 1.000 0.000 NA NA
## 19 Alignment ~~ PriceQuality -0.150 0.000 NA NA
## 20 PriceQuality ~~ PriceQuality 1.000 0.000 NA NA
semPaths(fit,"std",edge.label.cex=1,curvePivot=T,covAtResiduals=F,residuals=F,fade=F)
inspect(fit,"theta")
## FrUSMP Qualty PrchIn WOM Algnmn PrcQlt
## FreqUseSMP 4.150
## Quality 0.000 1.339
## PurchInt 0.000 0.000 2.998
## WOM 0.000 0.000 1.799 2.834
## Alignment 0.000 0.000 0.000 0.000 0.250
## PriceQuality 0.000 0.000 0.000 0.000 -0.154 4.187
Age<-t.test(Age~SMP,data=MainStudyCredence)
Gender<-chisq.test(MainStudyCredence$SMP,MainStudyCredence$Gender)
Income<-t.test(Income~SMP,data=MainStudyCredence)
Education<-t.test(Education~SMP,data=MainStudyCredence)
RE<-chisq.test(MainStudyCredence$SMP,MainStudyCredence$RE,simulate.p.value=T)
StimuliTime<-t.test(PageSubmitStimuli~SMP,data=MainStudyCredence,mu=1)
FreqUseSMP<-t.test(FreqUseSMP~SMP,data=MainStudyCredence)
Risk<-t.test(Risk~SMP,data=MainStudyCredence)
UsefulSMP<-t.test(UsefulSMP~SMP,data=MainStudyCredence)
BrandFam<-t.test(BrandFam~SMP,data=MainStudyCredence)
PriceQuality<-t.test(PriceQuality~SMP,data=MainStudyCredence)
TextVideo<-t.test(TextVideo~SMP,data=MainStudyCredence)
PeersExperts<-t.test(PeersExperts~SMP,data=MainStudyCredence)
FreqPurchProduct<-t.test(FreqPurchProduct~SMP,data=MainStudyCredence)
ProductImportance<-t.test(ProductImportance~SMP,data=MainStudyCredence)
AnnualExpenses<-t.test(AnnualExpenses~SMP,data=MainStudyCredence)
FreqPurchProductOnline<-t.test(FreqPurchProductOnline~SMP,data=MainStudyCredence)
t1Stimuli<-t.test(t1Stimuli~SMP,data=MainStudyCredence)
t2Stimuli<-t.test(t2Stimuli~SMP,data=MainStudyCredence)
PageSubmitStimuli<-t.test(PageSubmitStimuli~SMP,data=MainStudyCredence)
ClicksStimuli<-t.test(ClicksStimuli~SMP,data=MainStudyCredence)
Threshold<-t.test(Threshold~SMP,data=MainStudyCredence)
Longitude<-t.test(LocationLongitude~SMP,data=MainStudyCredence)
Latitude<-t.test(LocationLatitude~SMP,data=MainStudyCredence)
controls<-t(data.frame(Age$p.value,Gender$p.value,Income$p.value,Education$p.value,RE$p.value,StimuliTime$p.value,FreqUseSMP$p.value,Risk$p.value,UsefulSMP$p.value,BrandFam$p.value,PriceQuality$p.value,TextVideo$p.value,PeersExperts$p.value,FreqPurchProduct$p.value,ProductImportance$p.value,AnnualExpenses$p.value,FreqPurchProductOnline$p.value,t1Stimuli$p.value,t2Stimuli$p.value,PageSubmitStimuli$p.value,ClicksStimuli$p.value,Threshold$p.value,Longitude$p.value,Latitude$p.value))
subset(controls,controls<0.1)
## [,1]
## FreqUseSMP.p.value 4.049070e-23
## UsefulSMP.p.value 6.046862e-20
## ProductImportance.p.value 4.405458e-02
leveneTest(Quality~SMP,data=MainStudyCredence,center=mean)
## Levene's Test for Homogeneity of Variance (center = mean)
## Df F value Pr(>F)
## group 1 0.4377 0.5091
## 185
t.test(Quality~SMP,data=MainStudyCredence,var.equal=T) ## Hypothesis 3
##
## Two Sample t-test
##
## data: Quality by SMP
## t = -2.3045, df = 185, p-value = 0.0223
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.8478307 -0.0657360
## sample estimates:
## mean in group Twitter mean in group YouTube
## 5.080851 5.537634
wilcox.test(Quality~SMP,data=MainStudyCredence)
##
## Wilcoxon rank sum test with continuity correction
##
## data: Quality by SMP
## W = 3528.5, p-value = 0.02217
## alternative hypothesis: true location shift is not equal to 0
Model<-'FreqUseSMP ~ Alignment
Quality ~ FreqUseSMP + Alignment + ProductImportance
PurchInt ~ Quality+Alignment+FreqUseSMP + ProductImportance
WOM ~ Quality+Alignment+FreqUseSMP+ProductImportance'
fit<-sem(Model,data=MainStudyCredence)
fitMeasures(fit)
## npar fmin chisq
## 17.000 0.010 3.821
## df pvalue baseline.chisq
## 1.000 0.051 318.492
## baseline.df baseline.pvalue cfi
## 14.000 0.000 0.991
## tli nnfi rfi
## 0.870 0.870 0.832
## nfi pnfi ifi
## 0.988 0.071 0.991
## rni logl unrestricted.logl
## 0.991 -1960.077 -1958.167
## aic bic ntotal
## 3954.155 4009.084 187.000
## bic2 rmsea rmsea.ci.lower
## 3955.238 0.123 0.000
## rmsea.ci.upper rmsea.pvalue rmr
## 0.263 0.106 0.159
## rmr_nomean srmr srmr_bentler
## 0.159 0.027 0.027
## srmr_bentler_nomean srmr_bollen srmr_bollen_nomean
## 0.027 0.026 0.026
## srmr_mplus srmr_mplus_nomean cn_05
## 0.027 0.027 189.016
## cn_01 gfi agfi
## 325.738 0.991 0.815
## pgfi mfi ecvi
## 0.047 0.992 0.202
summary(fit,standardized=T,fit.measures=T,rsq=T)
## lavaan (0.5-22) converged normally after 40 iterations
##
## Number of observations 187
##
## Estimator ML
## Minimum Function Test Statistic 3.821
## Degrees of freedom 1
## P-value (Chi-square) 0.051
##
## Model test baseline model:
##
## Minimum Function Test Statistic 318.492
## Degrees of freedom 14
## P-value 0.000
##
## User model versus baseline model:
##
## Comparative Fit Index (CFI) 0.991
## Tucker-Lewis Index (TLI) 0.870
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -1960.077
## Loglikelihood unrestricted model (H1) -1958.167
##
## Number of free parameters 17
## Akaike (AIC) 3954.155
## Bayesian (BIC) 4009.084
## Sample-size adjusted Bayesian (BIC) 3955.238
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.123
## 90 Percent Confidence Interval 0.000 0.263
## P-value RMSEA <= 0.05 0.106
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.027
##
## Parameter Estimates:
##
## Information Expected
## Standard Errors Standard
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## FreqUseSMP ~
## Alignment 3.182 0.277 11.481 0.000 3.182 0.643
## Quality ~
## FreqUseSMP 0.110 0.051 2.179 0.029 0.110 0.200
## Alignment 0.046 0.252 0.181 0.857 0.046 0.017
## ProductImprtnc 0.081 0.038 2.108 0.035 0.081 0.150
## PurchInt ~
## Quality 0.533 0.088 6.090 0.000 0.533 0.390
## Alignment 0.366 0.302 1.213 0.225 0.366 0.098
## FreqUseSMP 0.038 0.061 0.620 0.535 0.038 0.051
## ProductImprtnc 0.175 0.046 3.769 0.000 0.175 0.238
## WOM ~
## Quality 0.875 0.088 9.921 0.000 0.875 0.572
## Alignment -0.063 0.304 -0.209 0.835 -0.063 -0.015
## FreqUseSMP 0.036 0.062 0.581 0.561 0.036 0.043
## ProductImprtnc 0.173 0.047 3.704 0.000 0.173 0.210
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .PurchInt ~~
## .WOM 0.942 0.194 4.854 0.000 0.942 0.380
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .FreqUseSMP 3.590 0.371 9.670 0.000 3.590 0.587
## .Quality 1.720 0.178 9.670 0.000 1.720 0.926
## .PurchInt 2.464 0.255 9.670 0.000 2.464 0.710
## .WOM 2.500 0.259 9.670 0.000 2.500 0.577
##
## R-Square:
## Estimate
## FreqUseSMP 0.413
## Quality 0.074
## PurchInt 0.290
## WOM 0.423
coef(fit)
## FreqUseSMP~Alignment Quality~FreqUseSMP
## 3.182 0.110
## Quality~Alignment Quality~ProductImportance
## 0.046 0.081
## PurchInt~Quality PurchInt~Alignment
## 0.533 0.366
## PurchInt~FreqUseSMP PurchInt~ProductImportance
## 0.038 0.175
## WOM~Quality WOM~Alignment
## 0.875 -0.063
## WOM~FreqUseSMP WOM~ProductImportance
## 0.036 0.173
## FreqUseSMP~~FreqUseSMP Quality~~Quality
## 3.590 1.720
## PurchInt~~PurchInt WOM~~WOM
## 2.464 2.500
## PurchInt~~WOM
## 0.942
standardizedSolution(fit)
## lhs op rhs est.std se z pvalue
## 1 FreqUseSMP ~ Alignment 0.643 0.038 16.830 0.000
## 2 Quality ~ FreqUseSMP 0.200 0.091 2.207 0.027
## 3 Quality ~ Alignment 0.017 0.092 0.181 0.857
## 4 Quality ~ ProductImportance 0.150 0.070 2.142 0.032
## 5 PurchInt ~ Quality 0.390 0.060 6.514 0.000
## 6 PurchInt ~ Alignment 0.098 0.081 1.217 0.224
## 7 PurchInt ~ FreqUseSMP 0.051 0.081 0.620 0.535
## 8 PurchInt ~ ProductImportance 0.238 0.061 3.910 0.000
## 9 WOM ~ Quality 0.572 0.049 11.704 0.000
## 10 WOM ~ Alignment -0.015 0.073 -0.209 0.835
## 11 WOM ~ FreqUseSMP 0.043 0.073 0.581 0.561
## 12 WOM ~ ProductImportance 0.210 0.055 3.797 0.000
## 13 FreqUseSMP ~~ FreqUseSMP 0.587 0.049 11.939 0.000
## 14 Quality ~~ Quality 0.926 0.036 25.510 0.000
## 15 PurchInt ~~ PurchInt 0.710 0.055 12.939 0.000
## 16 WOM ~~ WOM 0.577 0.054 10.595 0.000
## 17 PurchInt ~~ WOM 0.380 0.063 6.066 0.000
## 18 Alignment ~~ Alignment 1.000 0.000 NA NA
## 19 Alignment ~~ ProductImportance 0.147 0.000 NA NA
## 20 ProductImportance ~~ ProductImportance 1.000 0.000 NA NA
semPaths(fit,"std",edge.label.cex=1,curvePivot=T,covAtResiduals=F,residuals=F,fade=F)
inspect(fit,"theta")
## FrUSMP Qualty PrchIn WOM Algnmn PrdctI
## FreqUseSMP 3.590
## Quality 0.000 1.720
## PurchInt 0.000 0.000 2.464
## WOM 0.000 0.000 0.942 2.500
## Alignment 0.000 0.000 0.000 0.000 0.250
## ProductImportance 0.000 0.000 0.000 0.000 0.187 6.431
MainStudy<-rbind(MainStudySearch,MainStudyExperience,MainStudyCredence)
Age<-t.test(Age~Alignment,data=MainStudy)
Gender<-chisq.test(MainStudy$Alignment,MainStudy$Gender)
Income<-t.test(Income~Alignment,data=MainStudy)
Education<-t.test(Education~Alignment,data=MainStudy)
RE<-chisq.test(MainStudy$Alignment,MainStudy$RE,simulate.p.value=T)
StimuliTime<-t.test(PageSubmitStimuli~Alignment,data=MainStudy,mu=1)
FreqUseSMP<-t.test(FreqUseSMP~Alignment,data=MainStudy)
Risk<-t.test(Risk~Alignment,data=MainStudy)
UsefulSMP<-t.test(UsefulSMP~Alignment,data=MainStudy)
BrandFam<-t.test(BrandFam~Alignment,data=MainStudy)
PriceQuality<-t.test(PriceQuality~Alignment,data=MainStudy)
TextVideo<-t.test(TextVideo~Alignment,data=MainStudy)
PeersExperts<-t.test(PeersExperts~Alignment,data=MainStudy)
FreqPurchProduct<-t.test(FreqPurchProduct~Alignment,data=MainStudy)
ProductImportance<-t.test(ProductImportance~Alignment,data=MainStudy)
AnnualExpenses<-t.test(AnnualExpenses~Alignment,data=MainStudy)
FreqPurchProductOnline<-t.test(FreqPurchProductOnline~Alignment,data=MainStudy)
t1Stimuli<-t.test(t1Stimuli~Alignment,data=MainStudy)
t2Stimuli<-t.test(t2Stimuli~Alignment,data=MainStudy)
PageSubmitStimuli<-t.test(PageSubmitStimuli~Alignment,data=MainStudy)
ClicksStimuli<-t.test(ClicksStimuli~Alignment,data=MainStudy)
Threshold<-t.test(Threshold~Alignment,data=MainStudy)
Longitude<-t.test(LocationLongitude~Alignment,data=MainStudy)
Latitude<-t.test(LocationLatitude~Alignment,data=MainStudy)
controls<-t(data.frame(Age$p.value,Gender$p.value,Income$p.value,Education$p.value,RE$p.value,StimuliTime$p.value,FreqUseSMP$p.value,Risk$p.value,UsefulSMP$p.value,BrandFam$p.value,PriceQuality$p.value,TextVideo$p.value,PeersExperts$p.value,FreqPurchProduct$p.value,ProductImportance$p.value,AnnualExpenses$p.value,FreqPurchProductOnline$p.value,t1Stimuli$p.value,t2Stimuli$p.value,PageSubmitStimuli$p.value,ClicksStimuli$p.value,Threshold$p.value,Longitude$p.value,Latitude$p.value))
subset(controls,controls<0.1)
## [,1]
## FreqUseSMP.p.value 3.272569e-06
## UsefulSMP.p.value 1.217876e-05
## ProductImportance.p.value 3.282396e-02
Model<-'FreqUseSMP ~ a*Alignment
Quality ~ b*FreqUseSMP + c*Alignment
PurchInt ~ d*Quality + e*Alignment
WOM ~ f*Quality + g*Alignment
IndirectOnQuality:=a*b
DirectOnQuality:=c
TotalOnQuality:=c+a*b
IndirectOnPurchInt:=d*c
DirectOnPurchInt:=e
TotalOnPurchInt:=e+d*c
IndirectOnWOM:=f*c
DirectOnWOM:=g
TotalOnWOM:=g+f*c'
fit<-sem(Model,data=MainStudy)
fitMeasures(fit)
## npar fmin chisq
## 12.000 0.013 14.830
## df pvalue baseline.chisq
## 2.000 0.001 639.817
## baseline.df baseline.pvalue cfi
## 10.000 0.000 0.980
## tli nnfi rfi
## 0.898 0.898 0.884
## nfi pnfi ifi
## 0.977 0.195 0.980
## rni logl unrestricted.logl
## 0.980 -4695.620 -4688.205
## aic bic ntotal
## 9415.241 9467.154 559.000
## bic2 rmsea rmsea.ci.lower
## 9429.061 0.107 0.061
## rmsea.ci.upper rmsea.pvalue rmr
## 0.161 0.024 0.180
## rmr_nomean srmr srmr_bentler
## 0.180 0.040 0.040
## srmr_bentler_nomean srmr_bollen srmr_bollen_nomean
## 0.040 0.040 0.040
## srmr_mplus srmr_mplus_nomean cn_05
## 0.040 0.040 226.845
## cn_01 gfi agfi
## 348.178 0.987 0.903
## pgfi mfi ecvi
## 0.132 0.989 0.069
summary(fit,standardized=T,fit.measures=T,rsq=T)
## lavaan (0.5-22) converged normally after 38 iterations
##
## Number of observations 559
##
## Estimator ML
## Minimum Function Test Statistic 14.830
## Degrees of freedom 2
## P-value (Chi-square) 0.001
##
## Model test baseline model:
##
## Minimum Function Test Statistic 639.817
## Degrees of freedom 10
## P-value 0.000
##
## User model versus baseline model:
##
## Comparative Fit Index (CFI) 0.980
## Tucker-Lewis Index (TLI) 0.898
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -4695.620
## Loglikelihood unrestricted model (H1) -4688.205
##
## Number of free parameters 12
## Akaike (AIC) 9415.241
## Bayesian (BIC) 9467.154
## Sample-size adjusted Bayesian (BIC) 9429.061
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.107
## 90 Percent Confidence Interval 0.061 0.161
## P-value RMSEA <= 0.05 0.024
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.040
##
## Parameter Estimates:
##
## Information Expected
## Standard Errors Standard
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## FreqUseSMP ~
## Alignment (a) 0.895 0.190 4.719 0.000 0.895 0.196
## Quality ~
## FreqUseSMP (b) 0.078 0.025 3.083 0.002 0.078 0.130
## Alignment (c) 0.362 0.116 3.118 0.002 0.362 0.132
## PurchInt ~
## Quality (d) 0.631 0.054 11.711 0.000 0.631 0.446
## Alignment (e) 0.175 0.148 1.184 0.237 0.175 0.045
## WOM ~
## Quality (f) 0.906 0.053 17.201 0.000 0.906 0.589
## Alignment (g) 0.245 0.145 1.695 0.090 0.245 0.058
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .PurchInt ~~
## .WOM 1.601 0.141 11.357 0.000 1.601 0.548
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .FreqUseSMP 5.029 0.301 16.718 0.000 5.029 0.962
## .Quality 1.810 0.108 16.718 0.000 1.810 0.959
## .PurchInt 2.990 0.179 16.718 0.000 2.990 0.792
## .WOM 2.857 0.171 16.718 0.000 2.857 0.639
##
## R-Square:
## Estimate
## FreqUseSMP 0.038
## Quality 0.041
## PurchInt 0.208
## WOM 0.361
##
## Defined Parameters:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## IndirectOnQlty 0.070 0.027 2.581 0.010 0.070 0.025
## DirectOnQualty 0.362 0.116 3.118 0.002 0.362 0.132
## TotalOnQuality 0.432 0.115 3.763 0.000 0.432 0.157
## IndrctOnPrchIn 0.228 0.076 3.013 0.003 0.228 0.059
## DirctOnPrchInt 0.175 0.148 1.184 0.237 0.175 0.045
## TotalOnPrchInt 0.404 0.164 2.467 0.014 0.404 0.104
## IndirectOnWOM 0.328 0.107 3.068 0.002 0.328 0.078
## DirectOnWOM 0.245 0.145 1.695 0.090 0.245 0.058
## TotalOnWOM 0.573 0.178 3.229 0.001 0.573 0.136
coef(fit)
## a b c
## 0.895 0.078 0.362
## d e f
## 0.631 0.175 0.906
## g FreqUseSMP~~FreqUseSMP Quality~~Quality
## 0.245 5.029 1.810
## PurchInt~~PurchInt WOM~~WOM PurchInt~~WOM
## 2.990 2.857 1.601
standardizedSolution(fit)
## lhs op rhs est.std se z pvalue
## 1 FreqUseSMP ~ Alignment 0.196 0.040 4.858 0.000
## 2 Quality ~ FreqUseSMP 0.130 0.042 3.108 0.002
## 3 Quality ~ Alignment 0.132 0.042 3.157 0.002
## 4 PurchInt ~ Quality 0.446 0.034 13.044 0.000
## 5 PurchInt ~ Alignment 0.045 0.038 1.185 0.236
## 6 WOM ~ Quality 0.589 0.028 21.117 0.000
## 7 WOM ~ Alignment 0.058 0.034 1.698 0.089
## 8 FreqUseSMP ~~ FreqUseSMP 0.962 0.016 60.989 0.000
## 9 Quality ~~ Quality 0.959 0.016 58.592 0.000
## 10 PurchInt ~~ PurchInt 0.792 0.031 25.946 0.000
## 11 WOM ~~ WOM 0.639 0.032 19.684 0.000
## 12 PurchInt ~~ WOM 0.548 0.030 18.496 0.000
## 13 Alignment ~~ Alignment 1.000 0.000 NA NA
## 14 IndirectOnQuality := a*b 0.025 0.010 2.606 0.009
## 15 DirectOnQuality := c 0.132 0.042 3.157 0.002
## 16 TotalOnQuality := c+a*b 0.157 0.041 3.834 0.000
## 17 IndirectOnPurchInt := d*c 0.059 0.019 3.057 0.002
## 18 DirectOnPurchInt := e 0.045 0.038 1.185 0.236
## 19 TotalOnPurchInt := e+d*c 0.104 0.042 2.487 0.013
## 20 IndirectOnWOM := f*c 0.078 0.025 3.119 0.002
## 21 DirectOnWOM := g 0.058 0.034 1.698 0.089
## 22 TotalOnWOM := g+f*c 0.136 0.041 3.274 0.001
semPaths(fit,"std",edge.label.cex=1,curvePivot=T,covAtResiduals=F,residuals=F,fade=F)
inspect(fit,"theta")
## FrUSMP Qualty PrchIn WOM Algnmn
## FreqUseSMP 5.029
## Quality 0.000 1.810
## PurchInt 0.000 0.000 2.990
## WOM 0.000 0.000 1.601 2.857
## Alignment 0.000 0.000 0.000 0.000 0.250
Model<-'FreqUseSMP ~ a*Alignment+ProductImportance
Quality ~ b*FreqUseSMP + c*Alignment+ProductImportance
PurchInt ~ d*Quality + e*Alignment+ProductImportance
WOM ~ f*Quality + g*Alignment+ProductImportance
IndirectOnQuality:=a*b
DirectOnQuality:=c
TotalOnQuality:=c+a*b
IndirectOnPurchInt:=d*c
DirectOnPurchInt:=e
TotalOnPurchInt:=e+d*c
IndirectOnWOM:=f*c
DirectOnWOM:=g
TotalOnWOM:=g+f*c'
fit<-sem(Model,data=MainStudy)
fitMeasures(fit)
## npar fmin chisq
## 16.000 0.012 13.840
## df pvalue baseline.chisq
## 2.000 0.001 673.550
## baseline.df baseline.pvalue cfi
## 14.000 0.000 0.982
## tli nnfi rfi
## 0.874 0.874 0.856
## nfi pnfi ifi
## 0.979 0.140 0.982
## rni logl unrestricted.logl
## 0.982 -5914.664 -5907.744
## aic bic ntotal
## 11861.329 11930.547 559.000
## bic2 rmsea rmsea.ci.lower
## 11879.756 0.103 0.056
## rmsea.ci.upper rmsea.pvalue rmr
## 0.157 0.032 0.145
## rmr_nomean srmr srmr_bentler
## 0.145 0.032 0.032
## srmr_bentler_nomean srmr_bollen srmr_bollen_nomean
## 0.032 0.032 0.032
## srmr_mplus srmr_mplus_nomean cn_05
## 0.032 0.032 242.991
## cn_01 gfi agfi
## 372.998 0.988 0.873
## pgfi mfi ecvi
## 0.094 0.989 0.082
summary(fit,standardized=T,fit.measures=T,rsq=T)
## lavaan (0.5-22) converged normally after 39 iterations
##
## Number of observations 559
##
## Estimator ML
## Minimum Function Test Statistic 13.840
## Degrees of freedom 2
## P-value (Chi-square) 0.001
##
## Model test baseline model:
##
## Minimum Function Test Statistic 673.550
## Degrees of freedom 14
## P-value 0.000
##
## User model versus baseline model:
##
## Comparative Fit Index (CFI) 0.982
## Tucker-Lewis Index (TLI) 0.874
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -5914.664
## Loglikelihood unrestricted model (H1) -5907.744
##
## Number of free parameters 16
## Akaike (AIC) 11861.329
## Bayesian (BIC) 11930.547
## Sample-size adjusted Bayesian (BIC) 11879.756
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.103
## 90 Percent Confidence Interval 0.056 0.157
## P-value RMSEA <= 0.05 0.032
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.032
##
## Parameter Estimates:
##
## Information Expected
## Standard Errors Standard
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## FreqUseSMP ~
## Alignment (a) 0.861 0.190 4.538 0.000 0.861 0.188
## PrdctImprt 0.084 0.043 1.974 0.048 0.084 0.082
## Quality ~
## FreqUseSMP (b) 0.068 0.025 2.740 0.006 0.068 0.114
## Alignment (c) 0.323 0.114 2.828 0.005 0.323 0.117
## PrdctImprt 0.120 0.025 4.735 0.000 0.120 0.194
## PurchInt ~
## Quality (d) 0.600 0.055 10.972 0.000 0.600 0.424
## Alignment (e) 0.151 0.147 1.027 0.304 0.151 0.039
## PrdctImprt 0.093 0.034 2.781 0.005 0.093 0.107
## WOM ~
## Quality (f) 0.880 0.054 16.428 0.000 0.880 0.572
## Alignment (g) 0.225 0.144 1.559 0.119 0.225 0.053
## PrdctImprt 0.080 0.033 2.425 0.015 0.080 0.084
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .PurchInt ~~
## .WOM 1.566 0.139 11.270 0.000 1.566 0.542
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .FreqUseSMP 4.994 0.299 16.718 0.000 4.994 0.955
## .Quality 1.741 0.104 16.718 0.000 1.741 0.922
## .PurchInt 2.949 0.176 16.718 0.000 2.949 0.782
## .WOM 2.828 0.169 16.718 0.000 2.828 0.632
##
## R-Square:
## Estimate
## FreqUseSMP 0.045
## Quality 0.078
## PurchInt 0.218
## WOM 0.368
##
## Defined Parameters:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## IndirectOnQlty 0.059 0.025 2.345 0.019 0.059 0.021
## DirectOnQualty 0.323 0.114 2.828 0.005 0.323 0.117
## TotalOnQuality 0.382 0.113 3.382 0.001 0.382 0.139
## IndrctOnPrchIn 0.194 0.071 2.738 0.006 0.194 0.050
## DirctOnPrchInt 0.151 0.147 1.027 0.304 0.151 0.039
## TotalOnPrchInt 0.345 0.161 2.141 0.032 0.345 0.089
## IndirectOnWOM 0.284 0.102 2.787 0.005 0.284 0.067
## DirectOnWOM 0.225 0.144 1.559 0.119 0.225 0.053
## TotalOnWOM 0.509 0.175 2.914 0.004 0.509 0.120
coef(fit)
## a FreqUseSMP~ProductImportance
## 0.861 0.084
## b c
## 0.068 0.323
## Quality~ProductImportance d
## 0.120 0.600
## e PurchInt~ProductImportance
## 0.151 0.093
## f g
## 0.880 0.225
## WOM~ProductImportance FreqUseSMP~~FreqUseSMP
## 0.080 4.994
## Quality~~Quality PurchInt~~PurchInt
## 1.741 2.949
## WOM~~WOM PurchInt~~WOM
## 2.828 1.566
standardizedSolution(fit)
## lhs op rhs est.std se z pvalue
## 1 FreqUseSMP ~ Alignment 0.188 0.040 4.660 0.000
## 2 FreqUseSMP ~ ProductImportance 0.082 0.041 1.984 0.047
## 3 Quality ~ FreqUseSMP 0.114 0.041 2.756 0.006
## 4 Quality ~ Alignment 0.117 0.041 2.855 0.004
## 5 Quality ~ ProductImportance 0.194 0.040 4.869 0.000
## 6 PurchInt ~ Quality 0.424 0.035 12.012 0.000
## 7 PurchInt ~ Alignment 0.039 0.038 1.028 0.304
## 8 PurchInt ~ ProductImportance 0.107 0.038 2.802 0.005
## 9 WOM ~ Quality 0.572 0.029 19.643 0.000
## 10 WOM ~ Alignment 0.053 0.034 1.562 0.118
## 11 WOM ~ ProductImportance 0.084 0.034 2.435 0.015
## 12 FreqUseSMP ~~ FreqUseSMP 0.955 0.017 56.390 0.000
## 13 Quality ~~ Quality 0.922 0.021 42.925 0.000
## 14 PurchInt ~~ PurchInt 0.782 0.031 25.363 0.000
## 15 WOM ~~ WOM 0.632 0.032 19.550 0.000
## 16 PurchInt ~~ WOM 0.542 0.030 18.161 0.000
## 17 Alignment ~~ Alignment 1.000 0.000 NA NA
## 18 Alignment ~~ ProductImportance 0.090 0.000 NA NA
## 19 ProductImportance ~~ ProductImportance 1.000 0.000 NA NA
## 20 IndirectOnQuality := a*b 0.021 0.009 2.363 0.018
## 21 DirectOnQuality := c 0.117 0.041 2.855 0.004
## 22 TotalOnQuality := c+a*b 0.139 0.040 3.431 0.001
## 23 IndirectOnPurchInt := d*c 0.050 0.018 2.769 0.006
## 24 DirectOnPurchInt := e 0.039 0.038 1.028 0.304
## 25 TotalOnPurchInt := e+d*c 0.089 0.041 2.153 0.031
## 26 IndirectOnWOM := f*c 0.067 0.024 2.823 0.005
## 27 DirectOnWOM := g 0.053 0.034 1.562 0.118
## 28 TotalOnWOM := g+f*c 0.120 0.041 2.945 0.003
semPaths(fit,"std",edge.label.cex=1,curvePivot=T,covAtResiduals=F,residuals=F,fade=F)
inspect(fit,"theta")
## FrUSMP Qualty PrchIn WOM Algnmn PrdctI
## FreqUseSMP 4.994
## Quality 0.000 1.741
## PurchInt 0.000 0.000 2.949
## WOM 0.000 0.000 1.566 2.828
## Alignment 0.000 0.000 0.000 0.000 0.250
## ProductImportance 0.000 0.000 0.000 0.000 0.100 4.923
Model<-'FreqUseSMP~Alignment+Risk+ProductImportance
Quality ~ FreqUseSMP + Alignment + Risk + ProductImportance+PriceQuality+AnnualExpenses+PageSubmitStimuli+FreqPurchProductOnline+PeersExperts+Age+Gender+ClicksStimuli+LocationLatitude+LocationLongitude+t1Stimuli+t2Stimuli+Threshold+t7_2
PurchInt ~ Quality + Alignment +Risk + ProductImportance+PriceQuality+AnnualExpenses+PageSubmitStimuli+FreqPurchProductOnline++PeersExperts+Age+Gender+ClicksStimuli+LocationLatitude+LocationLongitude+t1Stimuli+t2Stimuli+Threshold+t7_2
WOM ~ Quality + Alignment + Risk +ProductImportance+PriceQuality+AnnualExpenses+PageSubmitStimuli+FreqPurchProductOnline+PeersExperts+Age+Gender+ClicksStimuli+LocationLatitude+LocationLongitude+t1Stimuli+t2Stimuli+Threshold+t7_2'
fit<-sem(Model,data=MainStudyExperience)
fitMeasures(fit)
## npar fmin chisq
## 62.000 0.104 33.089
## df pvalue baseline.chisq
## 16.000 0.007 306.626
## baseline.df baseline.pvalue cfi
## 74.000 0.000 0.927
## tli nnfi rfi
## 0.660 0.660 0.501
## nfi pnfi ifi
## 0.892 0.193 0.941
## rni logl unrestricted.logl
## 0.927 -8993.287 -8976.742
## aic bic ntotal
## 18110.573 18300.845 159.000
## bic2 rmsea rmsea.ci.lower
## 18104.581 0.082 0.041
## rmsea.ci.upper rmsea.pvalue rmr
## 0.122 0.089 0.934
## rmr_nomean srmr srmr_bentler
## 0.934 0.027 0.027
## srmr_bentler_nomean srmr_bollen srmr_bollen_nomean
## 0.027 0.027 0.027
## srmr_mplus srmr_mplus_nomean cn_05
## 0.027 0.027 127.361
## cn_01 gfi agfi
## 154.769 0.919 -0.172
## pgfi mfi ecvi
## 0.064 0.948 0.988
summary(fit,standardized=T,fit.measures=T,rsq=T)
## lavaan (0.5-22) converged normally after 145 iterations
##
## Number of observations 159
##
## Estimator ML
## Minimum Function Test Statistic 33.089
## Degrees of freedom 16
## P-value (Chi-square) 0.007
##
## Model test baseline model:
##
## Minimum Function Test Statistic 306.626
## Degrees of freedom 74
## P-value 0.000
##
## User model versus baseline model:
##
## Comparative Fit Index (CFI) 0.927
## Tucker-Lewis Index (TLI) 0.660
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -8993.287
## Loglikelihood unrestricted model (H1) -8976.742
##
## Number of free parameters 62
## Akaike (AIC) 18110.573
## Bayesian (BIC) 18300.845
## Sample-size adjusted Bayesian (BIC) 18104.581
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.082
## 90 Percent Confidence Interval 0.041 0.122
## P-value RMSEA <= 0.05 0.089
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.027
##
## Parameter Estimates:
##
## Information Expected
## Standard Errors Standard
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## FreqUseSMP ~
## Alignment 0.908 0.317 2.865 0.004 0.908 0.216
## Risk 0.150 0.076 1.976 0.048 0.150 0.149
## ProductImprtnc 0.157 0.079 1.983 0.047 0.157 0.150
## Quality ~
## FreqUseSMP 0.081 0.044 1.861 0.063 0.081 0.145
## Alignment -0.166 0.188 -0.878 0.380 -0.166 -0.070
## Risk 0.054 0.047 1.164 0.245 0.054 0.096
## ProductImprtnc 0.121 0.056 2.145 0.032 0.121 0.205
## PriceQuality -0.020 0.049 -0.411 0.681 -0.020 -0.035
## AnnualExpenses -0.004 0.005 -0.666 0.506 -0.004 -0.059
## PageSubmitStml -0.003 0.006 -0.539 0.590 -0.003 -0.044
## FrqPrchPrdctOn 0.045 0.062 0.722 0.471 0.045 0.065
## PeersExperts -0.050 0.041 -1.219 0.223 -0.050 -0.101
## Age 0.007 0.010 0.734 0.463 0.007 0.060
## Gender 0.481 0.193 2.493 0.013 0.481 0.204
## ClicksStimuli -0.109 0.123 -0.889 0.374 -0.109 -0.091
## LocationLatitd 0.012 0.017 0.705 0.481 0.012 0.058
## LocationLongtd 0.002 0.003 0.584 0.559 0.002 0.046
## t1Stimuli 0.000 0.020 0.005 0.996 0.000 0.000
## t2Stimuli 0.006 0.004 1.390 0.165 0.006 0.145
## Threshold -0.003 0.002 -1.783 0.075 -0.003 -0.160
## t7_2 0.006 0.010 0.575 0.565 0.006 0.052
## PurchInt ~
## Quality 0.615 0.109 5.627 0.000 0.615 0.377
## Alignment -0.097 0.257 -0.378 0.706 -0.097 -0.025
## Risk 0.000 0.065 0.007 0.995 0.000 0.000
## ProductImprtnc -0.002 0.079 -0.021 0.983 -0.002 -0.002
## PriceQuality 0.034 0.069 0.497 0.619 0.034 0.036
## AnnualExpenses 0.004 0.008 0.534 0.593 0.004 0.041
## PageSubmitStml -0.000 0.008 -0.028 0.977 -0.000 -0.002
## FrqPrchPrdctOn 0.281 0.087 3.230 0.001 0.281 0.249
## PeersExperts 0.211 0.058 3.635 0.000 0.211 0.258
## Age -0.003 0.014 -0.191 0.848 -0.003 -0.013
## Gender -0.165 0.274 -0.602 0.547 -0.165 -0.043
## ClicksStimuli 0.176 0.172 1.027 0.304 0.176 0.090
## LocationLatitd 0.008 0.024 0.343 0.731 0.008 0.024
## LocationLongtd 0.007 0.004 1.558 0.119 0.007 0.105
## t1Stimuli -0.031 0.027 -1.111 0.266 -0.031 -0.082
## t2Stimuli -0.010 0.006 -1.744 0.081 -0.010 -0.156
## Threshold 0.001 0.002 0.266 0.790 0.001 0.021
## t7_2 -0.013 0.014 -0.971 0.331 -0.013 -0.076
## WOM ~
## Quality 0.862 0.114 7.560 0.000 0.862 0.507
## Alignment 0.036 0.268 0.133 0.894 0.036 0.009
## Risk -0.077 0.068 -1.137 0.256 -0.077 -0.080
## ProductImprtnc 0.082 0.083 0.988 0.323 0.082 0.082
## PriceQuality 0.006 0.072 0.089 0.929 0.006 0.007
## AnnualExpenses 0.005 0.008 0.584 0.559 0.005 0.045
## PageSubmitStml -0.003 0.008 -0.369 0.712 -0.003 -0.026
## FrqPrchPrdctOn 0.107 0.091 1.176 0.240 0.107 0.091
## PeersExperts 0.079 0.060 1.313 0.189 0.079 0.093
## Age 0.006 0.015 0.434 0.665 0.006 0.030
## Gender 0.121 0.286 0.425 0.671 0.121 0.030
## ClicksStimuli 0.129 0.179 0.720 0.472 0.129 0.063
## LocationLatitd 0.018 0.025 0.745 0.456 0.018 0.052
## LocationLongtd 0.010 0.005 2.045 0.041 0.010 0.138
## t1Stimuli -0.014 0.029 -0.499 0.618 -0.014 -0.037
## t2Stimuli 0.002 0.006 0.350 0.726 0.002 0.031
## Threshold 0.000 0.002 0.008 0.994 0.000 0.001
## t7_2 0.023 0.014 1.651 0.099 0.023 0.129
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .PurchInt ~~
## .WOM 1.556 0.229 6.803 0.000 1.556 0.641
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .FreqUseSMP 3.948 0.443 8.916 0.000 3.948 0.898
## .Quality 1.199 0.135 8.916 0.000 1.199 0.867
## .PurchInt 2.327 0.261 8.916 0.000 2.327 0.631
## .WOM 2.534 0.284 8.916 0.000 2.534 0.634
##
## R-Square:
## Estimate
## FreqUseSMP 0.102
## Quality 0.133
## PurchInt 0.369
## WOM 0.366
coef(fit)
## FreqUseSMP~Alignment FreqUseSMP~Risk
## 0.908 0.150
## FreqUseSMP~ProductImportance Quality~FreqUseSMP
## 0.157 0.081
## Quality~Alignment Quality~Risk
## -0.166 0.054
## Quality~ProductImportance Quality~PriceQuality
## 0.121 -0.020
## Quality~AnnualExpenses Quality~PageSubmitStimuli
## -0.004 -0.003
## Quality~FreqPurchProductOnline Quality~PeersExperts
## 0.045 -0.050
## Quality~Age Quality~Gender
## 0.007 0.481
## Quality~ClicksStimuli Quality~LocationLatitude
## -0.109 0.012
## Quality~LocationLongitude Quality~t1Stimuli
## 0.002 0.000
## Quality~t2Stimuli Quality~Threshold
## 0.006 -0.003
## Quality~t7_2 PurchInt~Quality
## 0.006 0.615
## PurchInt~Alignment PurchInt~Risk
## -0.097 0.000
## PurchInt~ProductImportance PurchInt~PriceQuality
## -0.002 0.034
## PurchInt~AnnualExpenses PurchInt~PageSubmitStimuli
## 0.004 0.000
## PurchInt~FreqPurchProductOnline PurchInt~PeersExperts
## 0.281 0.211
## PurchInt~Age PurchInt~Gender
## -0.003 -0.165
## PurchInt~ClicksStimuli PurchInt~LocationLatitude
## 0.176 0.008
## PurchInt~LocationLongitude PurchInt~t1Stimuli
## 0.007 -0.031
## PurchInt~t2Stimuli PurchInt~Threshold
## -0.010 0.001
## PurchInt~t7_2 WOM~Quality
## -0.013 0.862
## WOM~Alignment WOM~Risk
## 0.036 -0.077
## WOM~ProductImportance WOM~PriceQuality
## 0.082 0.006
## WOM~AnnualExpenses WOM~PageSubmitStimuli
## 0.005 -0.003
## WOM~FreqPurchProductOnline WOM~PeersExperts
## 0.107 0.079
## WOM~Age WOM~Gender
## 0.006 0.121
## WOM~ClicksStimuli WOM~LocationLatitude
## 0.129 0.018
## WOM~LocationLongitude WOM~t1Stimuli
## 0.010 -0.014
## WOM~t2Stimuli WOM~Threshold
## 0.002 0.000
## WOM~t7_2 FreqUseSMP~~FreqUseSMP
## 0.023 3.948
## Quality~~Quality PurchInt~~PurchInt
## 1.199 2.327
## WOM~~WOM PurchInt~~WOM
## 2.534 1.556
standardizedSolution(fit)
## lhs op rhs est.std se z
## 1 FreqUseSMP ~ Alignment 0.216 0.073 2.967
## 2 FreqUseSMP ~ Risk 0.149 0.074 2.008
## 3 FreqUseSMP ~ ProductImportance 0.150 0.074 2.015
## 4 Quality ~ FreqUseSMP 0.145 0.077 1.876
## 5 Quality ~ Alignment -0.070 0.080 -0.881
## 6 Quality ~ Risk 0.096 0.082 1.170
## 7 Quality ~ ProductImportance 0.205 0.094 2.184
## 8 Quality ~ PriceQuality -0.035 0.086 -0.412
## 9 Quality ~ AnnualExpenses -0.059 0.089 -0.667
## 10 Quality ~ PageSubmitStimuli -0.044 0.081 -0.540
## 11 Quality ~ FreqPurchProductOnline 0.065 0.090 0.723
## 12 Quality ~ PeersExperts -0.101 0.082 -1.226
## 13 Quality ~ Age 0.060 0.081 0.735
## 14 Quality ~ Gender 0.204 0.080 2.556
## 15 Quality ~ ClicksStimuli -0.091 0.103 -0.892
## 16 Quality ~ LocationLatitude 0.058 0.082 0.706
## 17 Quality ~ LocationLongitude 0.046 0.079 0.584
## 18 Quality ~ t1Stimuli 0.000 0.086 0.005
## 19 Quality ~ t2Stimuli 0.145 0.103 1.400
## 20 Quality ~ Threshold -0.160 0.089 -1.805
## 21 Quality ~ t7_2 0.052 0.091 0.576
## 22 PurchInt ~ Quality 0.377 0.064 5.894
## 23 PurchInt ~ Alignment -0.025 0.067 -0.378
## 24 PurchInt ~ Risk 0.000 0.070 0.007
## 25 PurchInt ~ ProductImportance -0.002 0.082 -0.021
## 26 PurchInt ~ PriceQuality 0.036 0.073 0.497
## 27 PurchInt ~ AnnualExpenses 0.041 0.076 0.535
## 28 PurchInt ~ PageSubmitStimuli -0.002 0.070 -0.028
## 29 PurchInt ~ FreqPurchProductOnline 0.249 0.075 3.317
## 30 PurchInt ~ PeersExperts 0.258 0.069 3.761
## 31 PurchInt ~ Age -0.013 0.069 -0.191
## 32 PurchInt ~ Gender -0.043 0.071 -0.602
## 33 PurchInt ~ ClicksStimuli 0.090 0.088 1.030
## 34 PurchInt ~ LocationLatitude 0.024 0.070 0.343
## 35 PurchInt ~ LocationLongitude 0.105 0.067 1.568
## 36 PurchInt ~ t1Stimuli -0.082 0.073 -1.115
## 37 PurchInt ~ t2Stimuli -0.156 0.089 -1.757
## 38 PurchInt ~ Threshold 0.021 0.077 0.266
## 39 PurchInt ~ t7_2 -0.076 0.078 -0.974
## 40 WOM ~ Quality 0.507 0.060 8.465
## 41 WOM ~ Alignment 0.009 0.067 0.133
## 42 WOM ~ Risk -0.080 0.070 -1.140
## 43 WOM ~ ProductImportance 0.082 0.082 0.990
## 44 WOM ~ PriceQuality 0.007 0.073 0.089
## 45 WOM ~ AnnualExpenses 0.045 0.076 0.585
## 46 WOM ~ PageSubmitStimuli -0.026 0.070 -0.369
## 47 WOM ~ FreqPurchProductOnline 0.091 0.077 1.180
## 48 WOM ~ PeersExperts 0.093 0.071 1.319
## 49 WOM ~ Age 0.030 0.069 0.434
## 50 WOM ~ Gender 0.030 0.071 0.425
## 51 WOM ~ ClicksStimuli 0.063 0.088 0.721
## 52 WOM ~ LocationLatitude 0.052 0.070 0.746
## 53 WOM ~ LocationLongitude 0.138 0.067 2.066
## 54 WOM ~ t1Stimuli -0.037 0.074 -0.499
## 55 WOM ~ t2Stimuli 0.031 0.090 0.350
## 56 WOM ~ Threshold 0.001 0.077 0.008
## 57 WOM ~ t7_2 0.129 0.077 1.662
## 58 FreqUseSMP ~~ FreqUseSMP 0.898 0.044 20.225
## 59 Quality ~~ Quality 0.867 0.049 17.863
## 60 PurchInt ~~ PurchInt 0.631 0.058 10.832
## 61 WOM ~~ WOM 0.634 0.060 10.567
## 62 PurchInt ~~ WOM 0.641 0.047 13.705
## 63 Alignment ~~ Alignment 1.000 0.000 NA
## 64 Alignment ~~ Risk 0.067 0.000 NA
## 65 Alignment ~~ ProductImportance 0.076 0.000 NA
## 66 Alignment ~~ PriceQuality -0.150 0.000 NA
## 67 Alignment ~~ AnnualExpenses -0.005 0.000 NA
## 68 Alignment ~~ PageSubmitStimuli 0.030 0.000 NA
## 69 Alignment ~~ FreqPurchProductOnline 0.046 0.000 NA
## 70 Alignment ~~ PeersExperts 0.079 0.000 NA
## 71 Alignment ~~ Age 0.127 0.000 NA
## 72 Alignment ~~ Gender 0.019 0.000 NA
## 73 Alignment ~~ ClicksStimuli -0.010 0.000 NA
## 74 Alignment ~~ LocationLatitude 0.060 0.000 NA
## 75 Alignment ~~ LocationLongitude -0.031 0.000 NA
## 76 Alignment ~~ t1Stimuli -0.050 0.000 NA
## 77 Alignment ~~ t2Stimuli 0.041 0.000 NA
## 78 Alignment ~~ Threshold -0.077 0.000 NA
## 79 Alignment ~~ t7_2 0.064 0.000 NA
## 80 Risk ~~ Risk 1.000 0.000 NA
## 81 Risk ~~ ProductImportance 0.042 0.000 NA
## 82 Risk ~~ PriceQuality 0.012 0.000 NA
## 83 Risk ~~ AnnualExpenses 0.076 0.000 NA
## 84 Risk ~~ PageSubmitStimuli 0.025 0.000 NA
## 85 Risk ~~ FreqPurchProductOnline -0.035 0.000 NA
## 86 Risk ~~ PeersExperts 0.183 0.000 NA
## 87 Risk ~~ Age 0.100 0.000 NA
## 88 Risk ~~ Gender -0.133 0.000 NA
## 89 Risk ~~ ClicksStimuli -0.082 0.000 NA
## 90 Risk ~~ LocationLatitude -0.245 0.000 NA
## 91 Risk ~~ LocationLongitude 0.162 0.000 NA
## 92 Risk ~~ t1Stimuli 0.021 0.000 NA
## 93 Risk ~~ t2Stimuli 0.033 0.000 NA
## 94 Risk ~~ Threshold -0.031 0.000 NA
## 95 Risk ~~ t7_2 0.014 0.000 NA
## 96 ProductImportance ~~ ProductImportance 1.000 0.000 NA
## 97 ProductImportance ~~ PriceQuality 0.215 0.000 NA
## 98 ProductImportance ~~ AnnualExpenses 0.420 0.000 NA
## 99 ProductImportance ~~ PageSubmitStimuli 0.112 0.000 NA
## 100 ProductImportance ~~ FreqPurchProductOnline 0.486 0.000 NA
## 101 ProductImportance ~~ PeersExperts 0.137 0.000 NA
## 102 ProductImportance ~~ Age 0.064 0.000 NA
## 103 ProductImportance ~~ Gender -0.244 0.000 NA
## 104 ProductImportance ~~ ClicksStimuli -0.019 0.000 NA
## 105 ProductImportance ~~ LocationLatitude -0.068 0.000 NA
## 106 ProductImportance ~~ LocationLongitude 0.007 0.000 NA
## 107 ProductImportance ~~ t1Stimuli 0.034 0.000 NA
## 108 ProductImportance ~~ t2Stimuli 0.012 0.000 NA
## 109 ProductImportance ~~ Threshold 0.038 0.000 NA
## 110 ProductImportance ~~ t7_2 0.031 0.000 NA
## 111 PriceQuality ~~ PriceQuality 1.000 0.000 NA
## 112 PriceQuality ~~ AnnualExpenses 0.157 0.000 NA
## 113 PriceQuality ~~ PageSubmitStimuli 0.041 0.000 NA
## 114 PriceQuality ~~ FreqPurchProductOnline 0.306 0.000 NA
## 115 PriceQuality ~~ PeersExperts 0.211 0.000 NA
## 116 PriceQuality ~~ Age 0.166 0.000 NA
## 117 PriceQuality ~~ Gender 0.052 0.000 NA
## 118 PriceQuality ~~ ClicksStimuli -0.110 0.000 NA
## 119 PriceQuality ~~ LocationLatitude -0.128 0.000 NA
## 120 PriceQuality ~~ LocationLongitude -0.027 0.000 NA
## 121 PriceQuality ~~ t1Stimuli 0.034 0.000 NA
## 122 PriceQuality ~~ t2Stimuli -0.087 0.000 NA
## 123 PriceQuality ~~ Threshold -0.083 0.000 NA
## 124 PriceQuality ~~ t7_2 -0.032 0.000 NA
## 125 AnnualExpenses ~~ AnnualExpenses 1.000 0.000 NA
## 126 AnnualExpenses ~~ PageSubmitStimuli -0.062 0.000 NA
## 127 AnnualExpenses ~~ FreqPurchProductOnline 0.275 0.000 NA
## 128 AnnualExpenses ~~ PeersExperts -0.003 0.000 NA
## 129 AnnualExpenses ~~ Age -0.153 0.000 NA
## 130 AnnualExpenses ~~ Gender -0.064 0.000 NA
## 131 AnnualExpenses ~~ ClicksStimuli 0.052 0.000 NA
## 132 AnnualExpenses ~~ LocationLatitude -0.045 0.000 NA
## 133 AnnualExpenses ~~ LocationLongitude -0.075 0.000 NA
## 134 AnnualExpenses ~~ t1Stimuli 0.070 0.000 NA
## 135 AnnualExpenses ~~ t2Stimuli 0.100 0.000 NA
## 136 AnnualExpenses ~~ Threshold 0.189 0.000 NA
## 137 AnnualExpenses ~~ t7_2 0.074 0.000 NA
## 138 PageSubmitStimuli ~~ PageSubmitStimuli 1.000 0.000 NA
## 139 PageSubmitStimuli ~~ FreqPurchProductOnline 0.011 0.000 NA
## 140 PageSubmitStimuli ~~ PeersExperts -0.044 0.000 NA
## 141 PageSubmitStimuli ~~ Age 0.136 0.000 NA
## 142 PageSubmitStimuli ~~ Gender -0.028 0.000 NA
## 143 PageSubmitStimuli ~~ ClicksStimuli -0.021 0.000 NA
## 144 PageSubmitStimuli ~~ LocationLatitude 0.066 0.000 NA
## 145 PageSubmitStimuli ~~ LocationLongitude -0.012 0.000 NA
## 146 PageSubmitStimuli ~~ t1Stimuli 0.256 0.000 NA
## 147 PageSubmitStimuli ~~ t2Stimuli 0.132 0.000 NA
## 148 PageSubmitStimuli ~~ Threshold 0.056 0.000 NA
## 149 PageSubmitStimuli ~~ t7_2 0.295 0.000 NA
## 150 FreqPurchProductOnline ~~ FreqPurchProductOnline 1.000 0.000 NA
## 151 FreqPurchProductOnline ~~ PeersExperts 0.036 0.000 NA
## 152 FreqPurchProductOnline ~~ Age 0.120 0.000 NA
## 153 FreqPurchProductOnline ~~ Gender -0.198 0.000 NA
## 154 FreqPurchProductOnline ~~ ClicksStimuli -0.066 0.000 NA
## 155 FreqPurchProductOnline ~~ LocationLatitude -0.020 0.000 NA
## 156 FreqPurchProductOnline ~~ LocationLongitude 0.066 0.000 NA
## 157 FreqPurchProductOnline ~~ t1Stimuli -0.059 0.000 NA
## 158 FreqPurchProductOnline ~~ t2Stimuli -0.038 0.000 NA
## 159 FreqPurchProductOnline ~~ Threshold -0.007 0.000 NA
## 160 FreqPurchProductOnline ~~ t7_2 -0.012 0.000 NA
## 161 PeersExperts ~~ PeersExperts 1.000 0.000 NA
## 162 PeersExperts ~~ Age -0.031 0.000 NA
## 163 PeersExperts ~~ Gender 0.125 0.000 NA
## 164 PeersExperts ~~ ClicksStimuli 0.063 0.000 NA
## 165 PeersExperts ~~ LocationLatitude -0.199 0.000 NA
## 166 PeersExperts ~~ LocationLongitude 0.129 0.000 NA
## 167 PeersExperts ~~ t1Stimuli -0.167 0.000 NA
## 168 PeersExperts ~~ t2Stimuli 0.007 0.000 NA
## 169 PeersExperts ~~ Threshold -0.143 0.000 NA
## 170 PeersExperts ~~ t7_2 -0.147 0.000 NA
## 171 Age ~~ Age 1.000 0.000 NA
## 172 Age ~~ Gender -0.129 0.000 NA
## 173 Age ~~ ClicksStimuli 0.031 0.000 NA
## 174 Age ~~ LocationLatitude 0.087 0.000 NA
## 175 Age ~~ LocationLongitude 0.024 0.000 NA
## 176 Age ~~ t1Stimuli 0.127 0.000 NA
## 177 Age ~~ t2Stimuli 0.085 0.000 NA
## 178 Age ~~ Threshold 0.044 0.000 NA
## 179 Age ~~ t7_2 0.076 0.000 NA
## 180 Gender ~~ Gender 1.000 0.000 NA
## 181 Gender ~~ ClicksStimuli -0.035 0.000 NA
## 182 Gender ~~ LocationLatitude -0.066 0.000 NA
## 183 Gender ~~ LocationLongitude 0.065 0.000 NA
## 184 Gender ~~ t1Stimuli -0.017 0.000 NA
## 185 Gender ~~ t2Stimuli -0.081 0.000 NA
## 186 Gender ~~ Threshold -0.137 0.000 NA
## 187 Gender ~~ t7_2 0.018 0.000 NA
## 188 ClicksStimuli ~~ ClicksStimuli 1.000 0.000 NA
## 189 ClicksStimuli ~~ LocationLatitude 0.032 0.000 NA
## 190 ClicksStimuli ~~ LocationLongitude 0.006 0.000 NA
## 191 ClicksStimuli ~~ t1Stimuli 0.177 0.000 NA
## 192 ClicksStimuli ~~ t2Stimuli 0.660 0.000 NA
## 193 ClicksStimuli ~~ Threshold 0.145 0.000 NA
## 194 ClicksStimuli ~~ t7_2 -0.102 0.000 NA
## 195 LocationLatitude ~~ LocationLatitude 1.000 0.000 NA
## 196 LocationLatitude ~~ LocationLongitude -0.246 0.000 NA
## 197 LocationLatitude ~~ t1Stimuli 0.096 0.000 NA
## 198 LocationLatitude ~~ t2Stimuli 0.041 0.000 NA
## 199 LocationLatitude ~~ Threshold 0.161 0.000 NA
## 200 LocationLatitude ~~ t7_2 0.055 0.000 NA
## 201 LocationLongitude ~~ LocationLongitude 1.000 0.000 NA
## 202 LocationLongitude ~~ t1Stimuli -0.047 0.000 NA
## 203 LocationLongitude ~~ t2Stimuli 0.001 0.000 NA
## 204 LocationLongitude ~~ Threshold 0.021 0.000 NA
## 205 LocationLongitude ~~ t7_2 -0.061 0.000 NA
## 206 t1Stimuli ~~ t1Stimuli 1.000 0.000 NA
## 207 t1Stimuli ~~ t2Stimuli 0.302 0.000 NA
## 208 t1Stimuli ~~ Threshold 0.286 0.000 NA
## 209 t1Stimuli ~~ t7_2 0.335 0.000 NA
## 210 t2Stimuli ~~ t2Stimuli 1.000 0.000 NA
## 211 t2Stimuli ~~ Threshold 0.195 0.000 NA
## 212 t2Stimuli ~~ t7_2 0.043 0.000 NA
## 213 Threshold ~~ Threshold 1.000 0.000 NA
## 214 Threshold ~~ t7_2 0.429 0.000 NA
## 215 t7_2 ~~ t7_2 1.000 0.000 NA
## pvalue
## 1 0.003
## 2 0.045
## 3 0.044
## 4 0.061
## 5 0.378
## 6 0.242
## 7 0.029
## 8 0.681
## 9 0.505
## 10 0.589
## 11 0.470
## 12 0.220
## 13 0.462
## 14 0.011
## 15 0.372
## 16 0.480
## 17 0.559
## 18 0.996
## 19 0.161
## 20 0.071
## 21 0.565
## 22 0.000
## 23 0.706
## 24 0.995
## 25 0.983
## 26 0.619
## 27 0.593
## 28 0.977
## 29 0.001
## 30 0.000
## 31 0.848
## 32 0.547
## 33 0.303
## 34 0.731
## 35 0.117
## 36 0.265
## 37 0.079
## 38 0.790
## 39 0.330
## 40 0.000
## 41 0.894
## 42 0.254
## 43 0.322
## 44 0.929
## 45 0.559
## 46 0.712
## 47 0.238
## 48 0.187
## 49 0.664
## 50 0.670
## 51 0.471
## 52 0.456
## 53 0.039
## 54 0.618
## 55 0.726
## 56 0.994
## 57 0.097
## 58 0.000
## 59 0.000
## 60 0.000
## 61 0.000
## 62 0.000
## 63 NA
## 64 NA
## 65 NA
## 66 NA
## 67 NA
## 68 NA
## 69 NA
## 70 NA
## 71 NA
## 72 NA
## 73 NA
## 74 NA
## 75 NA
## 76 NA
## 77 NA
## 78 NA
## 79 NA
## 80 NA
## 81 NA
## 82 NA
## 83 NA
## 84 NA
## 85 NA
## 86 NA
## 87 NA
## 88 NA
## 89 NA
## 90 NA
## 91 NA
## 92 NA
## 93 NA
## 94 NA
## 95 NA
## 96 NA
## 97 NA
## 98 NA
## 99 NA
## 100 NA
## 101 NA
## 102 NA
## 103 NA
## 104 NA
## 105 NA
## 106 NA
## 107 NA
## 108 NA
## 109 NA
## 110 NA
## 111 NA
## 112 NA
## 113 NA
## 114 NA
## 115 NA
## 116 NA
## 117 NA
## 118 NA
## 119 NA
## 120 NA
## 121 NA
## 122 NA
## 123 NA
## 124 NA
## 125 NA
## 126 NA
## 127 NA
## 128 NA
## 129 NA
## 130 NA
## 131 NA
## 132 NA
## 133 NA
## 134 NA
## 135 NA
## 136 NA
## 137 NA
## 138 NA
## 139 NA
## 140 NA
## 141 NA
## 142 NA
## 143 NA
## 144 NA
## 145 NA
## 146 NA
## 147 NA
## 148 NA
## 149 NA
## 150 NA
## 151 NA
## 152 NA
## 153 NA
## 154 NA
## 155 NA
## 156 NA
## 157 NA
## 158 NA
## 159 NA
## 160 NA
## 161 NA
## 162 NA
## 163 NA
## 164 NA
## 165 NA
## 166 NA
## 167 NA
## 168 NA
## 169 NA
## 170 NA
## 171 NA
## 172 NA
## 173 NA
## 174 NA
## 175 NA
## 176 NA
## 177 NA
## 178 NA
## 179 NA
## 180 NA
## 181 NA
## 182 NA
## 183 NA
## 184 NA
## 185 NA
## 186 NA
## 187 NA
## 188 NA
## 189 NA
## 190 NA
## 191 NA
## 192 NA
## 193 NA
## 194 NA
## 195 NA
## 196 NA
## 197 NA
## 198 NA
## 199 NA
## 200 NA
## 201 NA
## 202 NA
## 203 NA
## 204 NA
## 205 NA
## 206 NA
## 207 NA
## 208 NA
## 209 NA
## 210 NA
## 211 NA
## 212 NA
## 213 NA
## 214 NA
## 215 NA
semPaths(fit,"std",edge.label.cex=1,curvePivot=T,covAtResiduals=F,residuals=F,fade=F)
inspect(fit,"theta")
## FrUSMP Qualty PrchIn WOM Algnmn
## FreqUseSMP 3.948
## Quality 0.000 1.199
## PurchInt 0.000 0.000 2.327
## WOM 0.000 0.000 1.556 2.534
## Alignment 0.000 0.000 0.000 0.000 0.250
## Risk 0.000 0.000 0.000 0.000 0.070
## ProductImportance 0.000 0.000 0.000 0.000 0.076
## PriceQuality 0.000 0.000 0.000 0.000 -0.154
## AnnualExpenses 0.000 0.000 0.000 0.000 -0.046
## PageSubmitStimuli 0.000 0.000 0.000 0.000 0.256
## FreqPurchProductOnline 0.000 0.000 0.000 0.000 0.039
## PeersExperts 0.000 0.000 0.000 0.000 0.092
## Age 0.000 0.000 0.000 0.000 0.603
## Gender 0.000 0.000 0.000 0.000 0.005
## ClicksStimuli 0.000 0.000 0.000 0.000 -0.005
## LocationLatitude 0.000 0.000 0.000 0.000 0.171
## LocationLongitude 0.000 0.000 0.000 0.000 -0.452
## t1Stimuli 0.000 0.000 0.000 0.000 -0.127
## t2Stimuli 0.000 0.000 0.000 0.000 0.600
## Threshold 0.000 0.000 0.000 0.000 -2.417
## t7_2 0.000 0.000 0.000 0.000 0.352
## Risk PrdctI PrcQlt AnnlEx PgSbmS
## FreqUseSMP
## Quality
## PurchInt
## WOM
## Alignment
## Risk 4.309
## ProductImportance 0.173 3.984
## PriceQuality 0.050 0.876 4.187
## AnnualExpenses 3.070 16.220 6.216 374.215
## PageSubmitStimuli 0.878 3.751 1.395 -20.319 283.059
## FreqPurchProductOnline -0.122 1.648 1.064 9.054 0.308
## PeersExperts 0.892 0.642 1.016 -0.145 -1.757
## Age 1.984 1.208 3.231 -28.206 21.810
## Gender -0.138 -0.243 0.053 -0.614 -0.238
## ClicksStimuli -0.168 -0.037 -0.222 0.993 -0.351
## LocationLatitude -2.897 -0.773 -1.494 -4.972 6.341
## LocationLongitude 9.701 0.410 -1.568 -41.598 -5.957
## t1Stimuli 0.223 0.348 0.353 6.968 22.145
## t2Stimuli 2.022 0.703 -5.195 56.306 64.921
## Threshold -4.088 4.803 -10.646 229.003 58.746
## t7_2 0.310 0.676 -0.709 15.733 54.392
## FrqPPO PrsExp Age Gender ClcksS
## FreqUseSMP
## Quality
## PurchInt
## WOM
## Alignment
## Risk
## ProductImportance
## PriceQuality
## AnnualExpenses
## PageSubmitStimuli
## FreqPurchProductOnline 2.890
## PeersExperts 0.145 5.535
## Age 1.946 -0.685 90.726
## Gender -0.168 0.147 -0.612 0.249
## ClicksStimuli -0.110 0.145 0.286 -0.017 0.967
## LocationLatitude -0.191 -2.669 4.694 -0.186 0.179
## LocationLongitude 3.226 8.764 6.611 0.942 0.157
## t1Stimuli -0.516 -2.019 6.225 -0.043 0.892
## t2Stimuli -1.899 0.477 23.753 -1.178 18.924
## Threshold -0.735 -21.077 26.159 -4.262 8.927
## t7_2 -0.232 -3.799 7.923 0.098 -1.105
## LctnLt LctnLn t1Stml t2Stml Thrshl
## FreqUseSMP
## Quality
## PurchInt
## WOM
## Alignment
## Risk
## ProductImportance
## PriceQuality
## AnnualExpenses
## PageSubmitStimuli
## FreqPurchProductOnline
## PeersExperts
## Age
## Gender
## ClicksStimuli
## LocationLatitude 32.458
## LocationLongitude -40.398 832.226
## t1Stimuli 2.813 -7.020 26.367
## t2Stimuli 6.892 0.789 45.235 851.397
## Threshold 57.577 38.158 91.959 356.721 3916.373
## t7_2 3.445 -19.287 18.861 13.832 294.176
## t7_2
## FreqUseSMP
## Quality
## PurchInt
## WOM
## Alignment
## Risk
## ProductImportance
## PriceQuality
## AnnualExpenses
## PageSubmitStimuli
## FreqPurchProductOnline
## PeersExperts
## Age
## Gender
## ClicksStimuli
## LocationLatitude
## LocationLongitude
## t1Stimuli
## t2Stimuli
## Threshold
## t7_2 120.301
Model<-'FreqUseSMP~Alignment+Risk
Quality ~ FreqUseSMP + Alignment + Risk + PageSubmitStimuli+Age+Gender+ClicksStimuli+LocationLatitude+LocationLongitude+t1Stimuli+t2Stimuli+Threshold+t7_2
PurchInt ~ Quality + Alignment +Risk + +PageSubmitStimuli+Age+Gender+ClicksStimuli+LocationLatitude+LocationLongitude+t1Stimuli+t2Stimuli+Threshold+t7_2
WOM ~ Quality + Alignment + Risk +AnnualExpenses+PageSubmitStimuli+Age+Gender+ClicksStimuli+LocationLatitude+LocationLongitude+t1Stimuli+t2Stimuli+Threshold+t7_2'
fit<-sem(Model,data=MainStudyExperience)
fitMeasures(fit)
## npar fmin chisq
## 47.000 0.102 32.348
## df pvalue baseline.chisq
## 15.000 0.006 258.456
## baseline.df baseline.pvalue cfi
## 58.000 0.000 0.913
## tli nnfi rfi
## 0.665 0.665 0.516
## nfi pnfi ifi
## 0.875 0.226 0.929
## rni logl unrestricted.logl
## 0.913 -7760.981 -7744.807
## aic bic ntotal
## 15615.962 15760.201 159.000
## bic2 rmsea rmsea.ci.lower
## 15611.420 0.085 0.044
## rmsea.ci.upper rmsea.pvalue rmr
## 0.126 0.074 1.360
## rmr_nomean srmr srmr_bentler
## 1.360 0.033 0.033
## srmr_bentler_nomean srmr_bollen srmr_bollen_nomean
## 0.033 0.033 0.033
## srmr_mplus srmr_mplus_nomean cn_05
## 0.033 0.033 123.864
## cn_01 gfi agfi
## 151.302 0.913 0.117
## pgfi mfi ecvi
## 0.090 0.947 0.795
summary(fit,standardized=T,fit.measures=T,rsq=T)
## lavaan (0.5-22) converged normally after 133 iterations
##
## Number of observations 159
##
## Estimator ML
## Minimum Function Test Statistic 32.348
## Degrees of freedom 15
## P-value (Chi-square) 0.006
##
## Model test baseline model:
##
## Minimum Function Test Statistic 258.456
## Degrees of freedom 58
## P-value 0.000
##
## User model versus baseline model:
##
## Comparative Fit Index (CFI) 0.913
## Tucker-Lewis Index (TLI) 0.665
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -7760.981
## Loglikelihood unrestricted model (H1) -7744.807
##
## Number of free parameters 47
## Akaike (AIC) 15615.962
## Bayesian (BIC) 15760.201
## Sample-size adjusted Bayesian (BIC) 15611.420
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.085
## 90 Percent Confidence Interval 0.044 0.126
## P-value RMSEA <= 0.05 0.074
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.033
##
## Parameter Estimates:
##
## Information Expected
## Standard Errors Standard
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## FreqUseSMP ~
## Alignment 0.954 0.320 2.982 0.003 0.954 0.227
## Risk 0.156 0.077 2.025 0.043 0.156 0.154
## Quality ~
## FreqUseSMP 0.100 0.044 2.267 0.023 0.100 0.179
## Alignment -0.140 0.188 -0.745 0.456 -0.140 -0.059
## Risk 0.032 0.046 0.694 0.488 0.032 0.057
## PageSubmitStml -0.001 0.006 -0.205 0.838 -0.001 -0.017
## Age 0.009 0.010 0.886 0.376 0.009 0.070
## Gender 0.297 0.186 1.601 0.109 0.297 0.126
## ClicksStimuli -0.130 0.125 -1.040 0.298 -0.130 -0.108
## LocationLatitd 0.011 0.017 0.635 0.526 0.011 0.052
## LocationLongtd 0.002 0.003 0.616 0.538 0.002 0.049
## t1Stimuli 0.003 0.020 0.158 0.875 0.003 0.014
## t2Stimuli 0.006 0.004 1.321 0.186 0.006 0.140
## Threshold -0.003 0.002 -1.784 0.075 -0.003 -0.161
## t7_2 0.006 0.010 0.613 0.540 0.006 0.057
## PurchInt ~
## Quality 0.661 0.117 5.634 0.000 0.661 0.404
## Alignment -0.002 0.275 -0.008 0.994 -0.002 -0.001
## Risk 0.017 0.069 0.245 0.807 0.017 0.018
## PageSubmitStml 0.001 0.009 0.076 0.939 0.001 0.006
## Age 0.002 0.015 0.118 0.906 0.002 0.009
## Gender -0.247 0.281 -0.878 0.380 -0.247 -0.064
## ClicksStimuli 0.194 0.188 1.031 0.302 0.194 0.099
## LocationLatitd -0.009 0.026 -0.361 0.718 -0.009 -0.027
## LocationLongtd 0.009 0.005 1.792 0.073 0.009 0.131
## t1Stimuli -0.047 0.030 -1.573 0.116 -0.047 -0.125
## t2Stimuli -0.010 0.006 -1.614 0.106 -0.010 -0.159
## Threshold 0.001 0.003 0.212 0.832 0.001 0.018
## t7_2 -0.017 0.015 -1.155 0.248 -0.017 -0.099
## WOM ~
## Quality 0.907 0.114 7.994 0.000 0.907 0.536
## Alignment 0.106 0.266 0.399 0.690 0.106 0.027
## Risk -0.074 0.067 -1.108 0.268 -0.074 -0.077
## AnnualExpenses 0.003 0.005 0.627 0.531 0.003 0.032
## PageSubmitStml -0.002 0.008 -0.191 0.849 -0.002 -0.013
## Age 0.008 0.014 0.545 0.586 0.008 0.037
## Gender -0.002 0.272 -0.008 0.994 -0.002 -0.001
## ClicksStimuli 0.137 0.182 0.752 0.452 0.137 0.068
## LocationLatitd 0.009 0.025 0.350 0.727 0.009 0.025
## LocationLongtd 0.010 0.005 2.161 0.031 0.010 0.148
## t1Stimuli -0.020 0.029 -0.690 0.490 -0.020 -0.051
## t2Stimuli 0.002 0.006 0.289 0.772 0.002 0.027
## Threshold 0.000 0.003 0.056 0.955 0.000 0.004
## t7_2 0.021 0.015 1.480 0.139 0.021 0.118
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .PurchInt ~~
## .WOM 1.798 0.261 6.894 0.000 1.798 0.653
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .FreqUseSMP 4.046 0.454 8.916 0.000 4.046 0.920
## .Quality 1.261 0.141 8.916 0.000 1.261 0.909
## .PurchInt 2.844 0.319 8.916 0.000 2.844 0.768
## .WOM 2.665 0.299 8.916 0.000 2.665 0.670
##
## R-Square:
## Estimate
## FreqUseSMP 0.080
## Quality 0.091
## PurchInt 0.232
## WOM 0.330
coef(fit)
## FreqUseSMP~Alignment FreqUseSMP~Risk
## 0.954 0.156
## Quality~FreqUseSMP Quality~Alignment
## 0.100 -0.140
## Quality~Risk Quality~PageSubmitStimuli
## 0.032 -0.001
## Quality~Age Quality~Gender
## 0.009 0.297
## Quality~ClicksStimuli Quality~LocationLatitude
## -0.130 0.011
## Quality~LocationLongitude Quality~t1Stimuli
## 0.002 0.003
## Quality~t2Stimuli Quality~Threshold
## 0.006 -0.003
## Quality~t7_2 PurchInt~Quality
## 0.006 0.661
## PurchInt~Alignment PurchInt~Risk
## -0.002 0.017
## PurchInt~PageSubmitStimuli PurchInt~Age
## 0.001 0.002
## PurchInt~Gender PurchInt~ClicksStimuli
## -0.247 0.194
## PurchInt~LocationLatitude PurchInt~LocationLongitude
## -0.009 0.009
## PurchInt~t1Stimuli PurchInt~t2Stimuli
## -0.047 -0.010
## PurchInt~Threshold PurchInt~t7_2
## 0.001 -0.017
## WOM~Quality WOM~Alignment
## 0.907 0.106
## WOM~Risk WOM~AnnualExpenses
## -0.074 0.003
## WOM~PageSubmitStimuli WOM~Age
## -0.002 0.008
## WOM~Gender WOM~ClicksStimuli
## -0.002 0.137
## WOM~LocationLatitude WOM~LocationLongitude
## 0.009 0.010
## WOM~t1Stimuli WOM~t2Stimuli
## -0.020 0.002
## WOM~Threshold WOM~t7_2
## 0.000 0.021
## FreqUseSMP~~FreqUseSMP Quality~~Quality
## 4.046 1.261
## PurchInt~~PurchInt WOM~~WOM
## 2.844 2.665
## PurchInt~~WOM
## 1.798
standardizedSolution(fit)
## lhs op rhs est.std se z pvalue
## 1 FreqUseSMP ~ Alignment 0.227 0.073 3.101 0.002
## 2 FreqUseSMP ~ Risk 0.154 0.075 2.061 0.039
## 3 Quality ~ FreqUseSMP 0.179 0.078 2.299 0.021
## 4 Quality ~ Alignment -0.059 0.080 -0.747 0.455
## 5 Quality ~ Risk 0.057 0.082 0.695 0.487
## 6 Quality ~ PageSubmitStimuli -0.017 0.082 -0.205 0.838
## 7 Quality ~ Age 0.070 0.078 0.889 0.374
## 8 Quality ~ Gender 0.126 0.078 1.618 0.106
## 9 Quality ~ ClicksStimuli -0.108 0.104 -1.044 0.296
## 10 Quality ~ LocationLatitude 0.052 0.082 0.636 0.525
## 11 Quality ~ LocationLongitude 0.049 0.079 0.617 0.537
## 12 Quality ~ t1Stimuli 0.014 0.087 0.158 0.875
## 13 Quality ~ t2Stimuli 0.140 0.106 1.331 0.183
## 14 Quality ~ Threshold -0.161 0.089 -1.808 0.071
## 15 Quality ~ t7_2 0.057 0.093 0.614 0.539
## 16 PurchInt ~ Quality 0.404 0.067 6.070 0.000
## 17 PurchInt ~ Alignment -0.001 0.071 -0.008 0.994
## 18 PurchInt ~ Risk 0.018 0.075 0.245 0.807
## 19 PurchInt ~ PageSubmitStimuli 0.006 0.076 0.076 0.939
## 20 PurchInt ~ Age 0.009 0.072 0.118 0.906
## 21 PurchInt ~ Gender -0.064 0.073 -0.880 0.379
## 22 PurchInt ~ ClicksStimuli 0.099 0.096 1.035 0.301
## 23 PurchInt ~ LocationLatitude -0.027 0.076 -0.361 0.718
## 24 PurchInt ~ LocationLongitude 0.131 0.072 1.811 0.070
## 25 PurchInt ~ t1Stimuli -0.125 0.079 -1.586 0.113
## 26 PurchInt ~ t2Stimuli -0.159 0.097 -1.628 0.103
## 27 PurchInt ~ Threshold 0.018 0.084 0.212 0.832
## 28 PurchInt ~ t7_2 -0.099 0.085 -1.160 0.246
## 29 WOM ~ Quality 0.536 0.058 9.251 0.000
## 30 WOM ~ Alignment 0.027 0.067 0.399 0.690
## 31 WOM ~ Risk -0.077 0.070 -1.112 0.266
## 32 WOM ~ AnnualExpenses 0.032 0.052 0.627 0.531
## 33 WOM ~ PageSubmitStimuli -0.013 0.071 -0.191 0.849
## 34 WOM ~ Age 0.037 0.068 0.545 0.586
## 35 WOM ~ Gender -0.001 0.068 -0.008 0.994
## 36 WOM ~ ClicksStimuli 0.068 0.090 0.753 0.451
## 37 WOM ~ LocationLatitude 0.025 0.071 0.350 0.726
## 38 WOM ~ LocationLongitude 0.148 0.068 2.188 0.029
## 39 WOM ~ t1Stimuli -0.051 0.074 -0.691 0.490
## 40 WOM ~ t2Stimuli 0.027 0.092 0.289 0.772
## 41 WOM ~ Threshold 0.004 0.079 0.056 0.955
## 42 WOM ~ t7_2 0.118 0.079 1.489 0.137
## 43 FreqUseSMP ~~ FreqUseSMP 0.920 0.040 22.718 0.000
## 44 Quality ~~ Quality 0.909 0.043 21.301 0.000
## 45 PurchInt ~~ PurchInt 0.768 0.058 13.181 0.000
## 46 WOM ~~ WOM 0.670 0.061 11.016 0.000
## 47 PurchInt ~~ WOM 0.653 0.045 14.353 0.000
## 48 Alignment ~~ Alignment 1.000 0.000 NA NA
## 49 Alignment ~~ Risk 0.067 0.000 NA NA
## 50 Alignment ~~ PageSubmitStimuli 0.030 0.000 NA NA
## 51 Alignment ~~ Age 0.127 0.000 NA NA
## 52 Alignment ~~ Gender 0.019 0.000 NA NA
## 53 Alignment ~~ ClicksStimuli -0.010 0.000 NA NA
## 54 Alignment ~~ LocationLatitude 0.060 0.000 NA NA
## 55 Alignment ~~ LocationLongitude -0.031 0.000 NA NA
## 56 Alignment ~~ t1Stimuli -0.050 0.000 NA NA
## 57 Alignment ~~ t2Stimuli 0.041 0.000 NA NA
## 58 Alignment ~~ Threshold -0.077 0.000 NA NA
## 59 Alignment ~~ t7_2 0.064 0.000 NA NA
## 60 Alignment ~~ AnnualExpenses -0.005 0.000 NA NA
## 61 Risk ~~ Risk 1.000 0.000 NA NA
## 62 Risk ~~ PageSubmitStimuli 0.025 0.000 NA NA
## 63 Risk ~~ Age 0.100 0.000 NA NA
## 64 Risk ~~ Gender -0.133 0.000 NA NA
## 65 Risk ~~ ClicksStimuli -0.082 0.000 NA NA
## 66 Risk ~~ LocationLatitude -0.245 0.000 NA NA
## 67 Risk ~~ LocationLongitude 0.162 0.000 NA NA
## 68 Risk ~~ t1Stimuli 0.021 0.000 NA NA
## 69 Risk ~~ t2Stimuli 0.033 0.000 NA NA
## 70 Risk ~~ Threshold -0.031 0.000 NA NA
## 71 Risk ~~ t7_2 0.014 0.000 NA NA
## 72 Risk ~~ AnnualExpenses 0.076 0.000 NA NA
## 73 PageSubmitStimuli ~~ PageSubmitStimuli 1.000 0.000 NA NA
## 74 PageSubmitStimuli ~~ Age 0.136 0.000 NA NA
## 75 PageSubmitStimuli ~~ Gender -0.028 0.000 NA NA
## 76 PageSubmitStimuli ~~ ClicksStimuli -0.021 0.000 NA NA
## 77 PageSubmitStimuli ~~ LocationLatitude 0.066 0.000 NA NA
## 78 PageSubmitStimuli ~~ LocationLongitude -0.012 0.000 NA NA
## 79 PageSubmitStimuli ~~ t1Stimuli 0.256 0.000 NA NA
## 80 PageSubmitStimuli ~~ t2Stimuli 0.132 0.000 NA NA
## 81 PageSubmitStimuli ~~ Threshold 0.056 0.000 NA NA
## 82 PageSubmitStimuli ~~ t7_2 0.295 0.000 NA NA
## 83 PageSubmitStimuli ~~ AnnualExpenses -0.062 0.000 NA NA
## 84 Age ~~ Age 1.000 0.000 NA NA
## 85 Age ~~ Gender -0.129 0.000 NA NA
## 86 Age ~~ ClicksStimuli 0.031 0.000 NA NA
## 87 Age ~~ LocationLatitude 0.087 0.000 NA NA
## 88 Age ~~ LocationLongitude 0.024 0.000 NA NA
## 89 Age ~~ t1Stimuli 0.127 0.000 NA NA
## 90 Age ~~ t2Stimuli 0.085 0.000 NA NA
## 91 Age ~~ Threshold 0.044 0.000 NA NA
## 92 Age ~~ t7_2 0.076 0.000 NA NA
## 93 Age ~~ AnnualExpenses -0.153 0.000 NA NA
## 94 Gender ~~ Gender 1.000 0.000 NA NA
## 95 Gender ~~ ClicksStimuli -0.035 0.000 NA NA
## 96 Gender ~~ LocationLatitude -0.066 0.000 NA NA
## 97 Gender ~~ LocationLongitude 0.065 0.000 NA NA
## 98 Gender ~~ t1Stimuli -0.017 0.000 NA NA
## 99 Gender ~~ t2Stimuli -0.081 0.000 NA NA
## 100 Gender ~~ Threshold -0.137 0.000 NA NA
## 101 Gender ~~ t7_2 0.018 0.000 NA NA
## 102 Gender ~~ AnnualExpenses -0.064 0.000 NA NA
## 103 ClicksStimuli ~~ ClicksStimuli 1.000 0.000 NA NA
## 104 ClicksStimuli ~~ LocationLatitude 0.032 0.000 NA NA
## 105 ClicksStimuli ~~ LocationLongitude 0.006 0.000 NA NA
## 106 ClicksStimuli ~~ t1Stimuli 0.177 0.000 NA NA
## 107 ClicksStimuli ~~ t2Stimuli 0.660 0.000 NA NA
## 108 ClicksStimuli ~~ Threshold 0.145 0.000 NA NA
## 109 ClicksStimuli ~~ t7_2 -0.102 0.000 NA NA
## 110 ClicksStimuli ~~ AnnualExpenses 0.052 0.000 NA NA
## 111 LocationLatitude ~~ LocationLatitude 1.000 0.000 NA NA
## 112 LocationLatitude ~~ LocationLongitude -0.246 0.000 NA NA
## 113 LocationLatitude ~~ t1Stimuli 0.096 0.000 NA NA
## 114 LocationLatitude ~~ t2Stimuli 0.041 0.000 NA NA
## 115 LocationLatitude ~~ Threshold 0.161 0.000 NA NA
## 116 LocationLatitude ~~ t7_2 0.055 0.000 NA NA
## 117 LocationLatitude ~~ AnnualExpenses -0.045 0.000 NA NA
## 118 LocationLongitude ~~ LocationLongitude 1.000 0.000 NA NA
## 119 LocationLongitude ~~ t1Stimuli -0.047 0.000 NA NA
## 120 LocationLongitude ~~ t2Stimuli 0.001 0.000 NA NA
## 121 LocationLongitude ~~ Threshold 0.021 0.000 NA NA
## 122 LocationLongitude ~~ t7_2 -0.061 0.000 NA NA
## 123 LocationLongitude ~~ AnnualExpenses -0.075 0.000 NA NA
## 124 t1Stimuli ~~ t1Stimuli 1.000 0.000 NA NA
## 125 t1Stimuli ~~ t2Stimuli 0.302 0.000 NA NA
## 126 t1Stimuli ~~ Threshold 0.286 0.000 NA NA
## 127 t1Stimuli ~~ t7_2 0.335 0.000 NA NA
## 128 t1Stimuli ~~ AnnualExpenses 0.070 0.000 NA NA
## 129 t2Stimuli ~~ t2Stimuli 1.000 0.000 NA NA
## 130 t2Stimuli ~~ Threshold 0.195 0.000 NA NA
## 131 t2Stimuli ~~ t7_2 0.043 0.000 NA NA
## 132 t2Stimuli ~~ AnnualExpenses 0.100 0.000 NA NA
## 133 Threshold ~~ Threshold 1.000 0.000 NA NA
## 134 Threshold ~~ t7_2 0.429 0.000 NA NA
## 135 Threshold ~~ AnnualExpenses 0.189 0.000 NA NA
## 136 t7_2 ~~ t7_2 1.000 0.000 NA NA
## 137 t7_2 ~~ AnnualExpenses 0.074 0.000 NA NA
## 138 AnnualExpenses ~~ AnnualExpenses 1.000 0.000 NA NA
semPaths(fit,"std",edge.label.cex=1,curvePivot=T,covAtResiduals=F,residuals=F,fade=F)
inspect(fit,"theta")
## FrUSMP Qualty PrchIn WOM Algnmn Risk
## FreqUseSMP 4.046
## Quality 0.000 1.261
## PurchInt 0.000 0.000 2.844
## WOM 0.000 0.000 1.798 2.665
## Alignment 0.000 0.000 0.000 0.000 0.250
## Risk 0.000 0.000 0.000 0.000 0.070 4.309
## PageSubmitStimuli 0.000 0.000 0.000 0.000 0.256 0.878
## Age 0.000 0.000 0.000 0.000 0.603 1.984
## Gender 0.000 0.000 0.000 0.000 0.005 -0.138
## ClicksStimuli 0.000 0.000 0.000 0.000 -0.005 -0.168
## LocationLatitude 0.000 0.000 0.000 0.000 0.171 -2.897
## LocationLongitude 0.000 0.000 0.000 0.000 -0.452 9.701
## t1Stimuli 0.000 0.000 0.000 0.000 -0.127 0.223
## t2Stimuli 0.000 0.000 0.000 0.000 0.600 2.022
## Threshold 0.000 0.000 0.000 0.000 -2.417 -4.088
## t7_2 0.000 0.000 0.000 0.000 0.352 0.310
## AnnualExpenses 0.000 0.000 0.000 0.000 -0.046 3.070
## PgSbmS Age Gender ClcksS LctnLt LctnLn
## FreqUseSMP
## Quality
## PurchInt
## WOM
## Alignment
## Risk
## PageSubmitStimuli 283.059
## Age 21.810 90.726
## Gender -0.238 -0.612 0.249
## ClicksStimuli -0.351 0.286 -0.017 0.967
## LocationLatitude 6.341 4.694 -0.186 0.179 32.458
## LocationLongitude -5.957 6.611 0.942 0.157 -40.398 832.226
## t1Stimuli 22.145 6.225 -0.043 0.892 2.813 -7.020
## t2Stimuli 64.921 23.753 -1.178 18.924 6.892 0.789
## Threshold 58.746 26.159 -4.262 8.927 57.577 38.158
## t7_2 54.392 7.923 0.098 -1.105 3.445 -19.287
## AnnualExpenses -20.319 -28.206 -0.614 0.993 -4.972 -41.598
## t1Stml t2Stml Thrshl t7_2 AnnlEx
## FreqUseSMP
## Quality
## PurchInt
## WOM
## Alignment
## Risk
## PageSubmitStimuli
## Age
## Gender
## ClicksStimuli
## LocationLatitude
## LocationLongitude
## t1Stimuli 26.367
## t2Stimuli 45.235 851.397
## Threshold 91.959 356.721 3916.373
## t7_2 18.861 13.832 294.176 120.301
## AnnualExpenses 6.968 56.306 229.003 15.733 374.215
## Thus, the most parsimonious model is the following:
Model<-'FreqUseSMP ~ a*Alignment
Quality ~ b*FreqUseSMP + c*Alignment
PurchInt ~ d*Quality + e*Alignment
WOM ~ f*Quality + g*Alignment
IndirectOnQuality:=a*b
DirectOnQuality:=c
TotalOnQuality:=c+a*b
IndirectOnPurchInt:=d*c
DirectOnPurchInt:=e
TotalOnPurchInt:=e+d*c
IndirectOnWOM:=f*c
DirectOnWOM:=g
TotalOnWOM:=g+f*c'
fit<-sem(Model,data=MainStudy)
fitMeasures(fit)
## npar fmin chisq
## 12.000 0.013 14.830
## df pvalue baseline.chisq
## 2.000 0.001 639.817
## baseline.df baseline.pvalue cfi
## 10.000 0.000 0.980
## tli nnfi rfi
## 0.898 0.898 0.884
## nfi pnfi ifi
## 0.977 0.195 0.980
## rni logl unrestricted.logl
## 0.980 -4695.620 -4688.205
## aic bic ntotal
## 9415.241 9467.154 559.000
## bic2 rmsea rmsea.ci.lower
## 9429.061 0.107 0.061
## rmsea.ci.upper rmsea.pvalue rmr
## 0.161 0.024 0.180
## rmr_nomean srmr srmr_bentler
## 0.180 0.040 0.040
## srmr_bentler_nomean srmr_bollen srmr_bollen_nomean
## 0.040 0.040 0.040
## srmr_mplus srmr_mplus_nomean cn_05
## 0.040 0.040 226.845
## cn_01 gfi agfi
## 348.178 0.987 0.903
## pgfi mfi ecvi
## 0.132 0.989 0.069
summary(fit,standardized=T,fit.measures=T,rsq=T)
## lavaan (0.5-22) converged normally after 38 iterations
##
## Number of observations 559
##
## Estimator ML
## Minimum Function Test Statistic 14.830
## Degrees of freedom 2
## P-value (Chi-square) 0.001
##
## Model test baseline model:
##
## Minimum Function Test Statistic 639.817
## Degrees of freedom 10
## P-value 0.000
##
## User model versus baseline model:
##
## Comparative Fit Index (CFI) 0.980
## Tucker-Lewis Index (TLI) 0.898
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -4695.620
## Loglikelihood unrestricted model (H1) -4688.205
##
## Number of free parameters 12
## Akaike (AIC) 9415.241
## Bayesian (BIC) 9467.154
## Sample-size adjusted Bayesian (BIC) 9429.061
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.107
## 90 Percent Confidence Interval 0.061 0.161
## P-value RMSEA <= 0.05 0.024
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.040
##
## Parameter Estimates:
##
## Information Expected
## Standard Errors Standard
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## FreqUseSMP ~
## Alignment (a) 0.895 0.190 4.719 0.000 0.895 0.196
## Quality ~
## FreqUseSMP (b) 0.078 0.025 3.083 0.002 0.078 0.130
## Alignment (c) 0.362 0.116 3.118 0.002 0.362 0.132
## PurchInt ~
## Quality (d) 0.631 0.054 11.711 0.000 0.631 0.446
## Alignment (e) 0.175 0.148 1.184 0.237 0.175 0.045
## WOM ~
## Quality (f) 0.906 0.053 17.201 0.000 0.906 0.589
## Alignment (g) 0.245 0.145 1.695 0.090 0.245 0.058
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .PurchInt ~~
## .WOM 1.601 0.141 11.357 0.000 1.601 0.548
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .FreqUseSMP 5.029 0.301 16.718 0.000 5.029 0.962
## .Quality 1.810 0.108 16.718 0.000 1.810 0.959
## .PurchInt 2.990 0.179 16.718 0.000 2.990 0.792
## .WOM 2.857 0.171 16.718 0.000 2.857 0.639
##
## R-Square:
## Estimate
## FreqUseSMP 0.038
## Quality 0.041
## PurchInt 0.208
## WOM 0.361
##
## Defined Parameters:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## IndirectOnQlty 0.070 0.027 2.581 0.010 0.070 0.025
## DirectOnQualty 0.362 0.116 3.118 0.002 0.362 0.132
## TotalOnQuality 0.432 0.115 3.763 0.000 0.432 0.157
## IndrctOnPrchIn 0.228 0.076 3.013 0.003 0.228 0.059
## DirctOnPrchInt 0.175 0.148 1.184 0.237 0.175 0.045
## TotalOnPrchInt 0.404 0.164 2.467 0.014 0.404 0.104
## IndirectOnWOM 0.328 0.107 3.068 0.002 0.328 0.078
## DirectOnWOM 0.245 0.145 1.695 0.090 0.245 0.058
## TotalOnWOM 0.573 0.178 3.229 0.001 0.573 0.136
coef(fit)
## a b c
## 0.895 0.078 0.362
## d e f
## 0.631 0.175 0.906
## g FreqUseSMP~~FreqUseSMP Quality~~Quality
## 0.245 5.029 1.810
## PurchInt~~PurchInt WOM~~WOM PurchInt~~WOM
## 2.990 2.857 1.601
standardizedSolution(fit)
## lhs op rhs est.std se z pvalue
## 1 FreqUseSMP ~ Alignment 0.196 0.040 4.858 0.000
## 2 Quality ~ FreqUseSMP 0.130 0.042 3.108 0.002
## 3 Quality ~ Alignment 0.132 0.042 3.157 0.002
## 4 PurchInt ~ Quality 0.446 0.034 13.044 0.000
## 5 PurchInt ~ Alignment 0.045 0.038 1.185 0.236
## 6 WOM ~ Quality 0.589 0.028 21.117 0.000
## 7 WOM ~ Alignment 0.058 0.034 1.698 0.089
## 8 FreqUseSMP ~~ FreqUseSMP 0.962 0.016 60.989 0.000
## 9 Quality ~~ Quality 0.959 0.016 58.592 0.000
## 10 PurchInt ~~ PurchInt 0.792 0.031 25.946 0.000
## 11 WOM ~~ WOM 0.639 0.032 19.684 0.000
## 12 PurchInt ~~ WOM 0.548 0.030 18.496 0.000
## 13 Alignment ~~ Alignment 1.000 0.000 NA NA
## 14 IndirectOnQuality := a*b 0.025 0.010 2.606 0.009
## 15 DirectOnQuality := c 0.132 0.042 3.157 0.002
## 16 TotalOnQuality := c+a*b 0.157 0.041 3.834 0.000
## 17 IndirectOnPurchInt := d*c 0.059 0.019 3.057 0.002
## 18 DirectOnPurchInt := e 0.045 0.038 1.185 0.236
## 19 TotalOnPurchInt := e+d*c 0.104 0.042 2.487 0.013
## 20 IndirectOnWOM := f*c 0.078 0.025 3.119 0.002
## 21 DirectOnWOM := g 0.058 0.034 1.698 0.089
## 22 TotalOnWOM := g+f*c 0.136 0.041 3.274 0.001
semPaths(fit,"std",edge.label.cex=1,curvePivot=T,covAtResiduals=F,residuals=F,fade=F)
inspect(fit,"theta")
## FrUSMP Qualty PrchIn WOM Algnmn
## FreqUseSMP 5.029
## Quality 0.000 1.810
## PurchInt 0.000 0.000 2.990
## WOM 0.000 0.000 1.601 2.857
## Alignment 0.000 0.000 0.000 0.000 0.250